ICEPAK 13.0: buone notizie per i progettisti elettronici

Transcription

Year 8 n°1 Spring 2011
ICEPAK 13.0:
buone notizie per i
progettisti elettronici
APERS
CALL FOR P
EN
IS NOW OP
CAE-based
tablet design
Combined 1D & 3D CFD approach
for GT Ventilation System analysis
Analisi di un meccanismo
link-drive per presse con tecnologia
multibody in ANSYS
Multi Variate Analysis in
Systematic Impeller Design Applying
modeFRONTIER at Sulzer Pumps
Interview with
Paolo Nesti,
Piaggio Group
Ottimizzazione
Termofluidodinamica
di un forno da
cucina Indesit
Newsletter EnginSoft Year 8 n°1 -
3
EnginSoft Flash
Researchers of Trinity College Dublin have
With this 1st edition of the Newsletter in
significantly improved the fatigue resistance
2011, we extend a Special Invitation to
of components using modeFRONTIER. GE Oil
our readers, to meet us at the EnginSoft
& Gas Italy adopted a combined 1D and 3D
International Conference 2011 from 20th
numerical approach with Flowmaster and
- 21st October in Verona. There could
ANSYS Fluent to study ventilation systems.
hardly be a better venue for the community
We interviewed Mr Paolo Nesti, engineer at
of simulation and VP (Virtual Prototyping)
Piaggio Group, one of the major players
users than Verona. A UNESCO world
worldwide in the two-wheeler vehicles
heritage site, famous for its operas, the
sector, and feature a case study on the use of
ancient amphitheatre built by the Romans,
ANSYS Workbench at Piaggio. Landi Renzo
Romeo and Juliet, and a diverse cultural
S.p.A., a global leader in components, LPG
wealth. Today, Verona is a vibrant city
and CNG fuel systems for motor vehicles,
dedicated to innovation. Verona’s airport
spoke to us about the use of modeFRONTIER
offers daily nonstop flights to Europe’s Ing. Stefano Odorizzi
in their product development. Componeering
hubs which will facilitate travel for our EnginSoft CEO and President
Inc. Finland presents the Opencell Delta™
guests from around the world!
concept which provides a brand new way to
The Conference, which is one of the major
construct metal sandwich panels.
Get-togethers for CAE and VP users worldwide, will again
The Event Calendar features conferences, fairs and courses
present a parallel event: the ANSYS Italian Users’ Meeting.
across Europe, in the USA and Japan...
EnginSoft is delighted to collaborate with ANSYS, Inc. and
When we hear about Japan in these days, above all our
ANSYS Italia, our key partners, to offer an interactive
heart and best wishes go out to the Japanese people who
platform to the ANSYS developers and users to share
battle and will overcome the consequences of a terrible
knowledge, experiences and to enhance the use of ANSYS
natural disaster that hit their country. Our Japan Column
in the various industrial fields.
brings to our readers an article on the novel approach of
In this edition, we report on the progress of the EnginSoft
CAE-based tablet design of Mr. Hideaki Sato of ASAHI
Americas Project. EnginSoft has recently strengthened its
BREWERIES, LTD. Elysium presents news on the use of
North American operations by expanding its base in Palo
ASFALIS at Nissan. We close the Column with an article on
Alto, Silicon Valley. Moreover, EnginSoft has joined the
Tokyo, a unique metropolis…and some ideas on how each
TFSA (Thermal and Fluid Sciences Affiliate) Program of
one of us can help.
Stanford University.
Finally, the Editorial Team would like to recommend the
Cascade Technologies, Inc, EnginSoft’s partner, is a spinnew book “Reactive Business Intelligence. From Data to
off of the Center for Turbulence Research at Stanford
Models to Insight” by Prof. Roberto Battiti and Prof.
University. Cascade develops and supports state of the art
Mauro Brunato to our readers. While the book is easy-toCFD analysis tools for various engineering applications. To
read, it guides us from the very basics to such advanced
stimulate the discussion on optimization, EnginSoft and
topics as supervised learning, data-mining, optimization,
Cascade have sponsored a One-Day Seminar on
statistics and interactive visualizations.
Optimization, which was held on 1st February at Stanford
To continue our discovery of the immense opportunities of
Campus. The driving force behind Cascade Technologies is
CAE and VP in our today’s world, EnginSoft and ANSYS
Prof. Gianluca Iaccarino, who was recently awarded the
invite our readers to the International Conference 2011.
Presidential Early Career Award for Scientists and
Please follow the Announcements, Call for Papers and
Engineers (PECASE) by President Barack Obama. Our
Program on www.caeconference.com
readers will find more information on Prof. Iaccarino’s
work and the prestigious award in this issue.
We look forward to welcoming you to Verona this October!
EnginSoft’s growing international business is also
reflected in the highlights of this issue: Sulzer Pumps, one
of the world's leading centrifugal pump manufacturers
Stefano Odorizzi
based in Winterthur, Switzerland, speaks about Multi
Editor in chief
Variate Analysis in Systematic Impeller Design.
4 - Newsletter EnginSoft Year 8 n°1
Sommario - Contents
CASE STUDIES
6
10
13
15
19
Multi Variate Analysis in Systematic Impeller Design Applying modeFRONTIER at Sulzer Pumps
Analisi di un meccanismo link-drive per presse con tecnologia multibody in ANSYS
Ottimizzazione termofluidodinamica di un forno da cucina Indesit
Combined 1D & 3D CFD Approach for GT Ventilation System Analysis
ANSYS WB and a Review of the Design Metrics in Piaggio: the Case of the Motor Shaft
INTERVIEWS
21
EnginSoft Interviews Ing. Paolo Nesti, Piaggio Group
CASE STUDIES
26
27
modeFRONTIER Used in the Design of Fatigue-Resistant Notches
A Multi-Objective Optimization with Open Source Software
SOFTWARE NEWS
32
33
36
38
ANSYS 13: Il punto sui solutori per modelli di grandi dimensioni nelle simulazioni meccaniche
La simulazione di sistema in ANSYS: Simplorer
ICEPAK 13.0: buone notizie per i progettisti elettronici
Development of the Novel Opencell™
IN DEPTH STUDIES
41
Componenti forgiati di qualità necessitano di un approccio CAE integrato – esperienze di simulazione di processo nel campo Energia e Nucleare
TESTIMONIAL
46
Landi Renzo: the global leader in the sector of components and LPG and CNG fuel systems
JAPAN CAE COLUMN
47
48
52
The CAD-CAM Cooperation in Nissan Achieved by ASFALIS
CAE-based tablet design
Tokyo a Metropolis
The EnginSoft Newsletter editions contain references to the following
products which are trademarks or registered trademarks of their respective owners:
ANSYS, ANSYS Workbench, AUTODYN, CFX, FLUENT and any and all
ANSYS, Inc. brand, product, service and feature names, logos and slogans are
registered trademarks or trademarks of ANSYS, Inc. or its subsidiaries in the
United States or other countries. [ICEM CFD is a trademark used by ANSYS,
Inc. under license]. (www.ANSYS.com)
modeFRONTIER is a trademark of ESTECO srl (www.esteco.com)
Flowmaster is a registered trademark of The Flowmaster Group BV in the
USA and Korea. (www.flowmaster.com)
MAGMASOFT is a trademark of MAGMA GmbH. (www.magmasoft.com)
ESAComp is a trademark of Componeering Inc.
(www.componeering.com)
Forge and Coldform are trademarks of Transvalor S.A.
(www.transvalor.com)
AdvantEdge is a trademark of Third Wave Systems
(www.thirdwavesys.com)
.
LS-DYNA is a trademark of Livermore Software Technology Corporation.
(www.lstc.com)
SCULPTOR is a trademark of Optimal Solutions Software, LLC
(www.optimalsolutions.us)
Grapheur is a product of Reactive Search SrL, a partner of EnginSoft
For more information, please contact the Editorial Team
PRESS RELEASE
54
56
President Obama Honors EnginSoft’s Partner with the
Presidential Early Career Award for Scientists and
Engineers
Formazione a distanza sugli elementi finiti
BOOK REVIEWS
57
REACTIVE BUSINESS INTELLIGENCE: From Data to
Models to Insight
60
61
62
Newsletter EnginSoft
Year 8 n°1 - Spring 2011
To receive a free copy of the next EnginSoft
Newsletters, please contact our Marketing office at:
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©Copyright EnginSoft Newsletter.
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EVENTS
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5
EnginSoft at the Optimization Day: Research and
Applications
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PAGE 6 MULTI VARIATE ANALYSIS IN
SYSTEMATIC IMPELLER DESIGN APPLYING
MODEFRONTIER AT SULZER PUMPS
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PAGE 15 COMBINED 1D & 3D CFD
APPROACH FOR GT VENTILATION
SYSTEM ANALYSIS
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PAGE 36 ICEPAK 13.0: BUONE NOTIZIE
PER I PROGETTISTI ELETTRONICI
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magazine published by EnginSoft SpA
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Multi Variate Analysis in
Systematic Impeller Design Applying
modeFRONTIER at Sulzer Pumps
The most important pump component - its heart - is the
impeller which transforms kinetic energy into pressure and
therefore generates the required head. The impeller
geometry is defined by more than 50 parameters requiring
experienced hydraulic design engineers. Even if only 20 of
these parameters have a major influence, it is obvious
that a severe variation yields an excessive database which
should be made use of.
Fig. 1 - Two stage pump with detailed view of the first stage impeller.
estimate for the new impeller and properly conditions the
variable ranges for an optimization which is likely to
follow. This article presents an approach based on
classification of existing impeller designs with Multi
Variate Analysis through Self Organizing Maps (SOM) by
use of modeFRONTIER.
Systematic impeller design
The parameters defining an impeller include the main
dimensions like outer diameter D2 and shaft diameter D0 as
also the meridional contour and blade shape (Figure 2).
The impeller design is done for a specified operating point
with given flow rate Q and head H for a certain rotational
speed n. Efficiency η is one criterion for an optimal
impeller design not only at best efficiency point bep but
also over a certain operating range (Figure 3, left).
Suction capability, which is the pressure available at pump
inlet NPSH, is another criterion (Figure 3, centre).
Decreasing NPSH affects the pump head which needs to be
considered.
Good suction capability and high efficiency both over a
broad operating range are conflictive design goals.
Increasing suction capability at maximum operating point
reduces efficiency at minimum operating point. This is an
important fact when using optimization techniques in
impeller design.
Fig. 2 - Dimensions of the impeller.
A proper classification of the available designs in the
database gives the developer a better understanding of
the complex parameter correlation and enables the
prediction of not yet available impellers by interpolating
among the existing designs. This gives a first parameter
Characteristic numbers
Impellers can be classified by characteristic numbers
enabling a comparison among the designs. The specific
speed nq defines the form of the impeller (Figure 4) and is
calculated from flow rate Q, head H and the rotational
speed n. Figure 5 lists the main design parameters and
shows their conversion into characteristic numbers. The
outer diameter D2 of the impeller is selected according an
Fig. 3 - left: Efficiency η; centre: suction capability NPSH within the operating range of the impeller dependent on the flow rate Q; right: NPSH3% criterion
optimal head coefficient Ψ for the specific speed nq. The
inlet diameter D1 influences the suction capability and
depends on the flow coefficient at inlet ϕ1. The suction
capability can either be expressed by a characteristic
number σ or the suction specific speed nss which both
depend on the suction head at pump inlet NPSH. Similar
relations exist for other dimensions.
Using these characteristic numbers and dimensionless
values, impellers with different outer diameters D2 can be
Fig. 4 - Impeller form in meridional view dependent on specific speed nq
compared and new designs can be calculated based on
these values. This facilitates a classification of the
impellers and the use of the SOM technique.
7
“pixel” being colored to reflect different properties of the
input data, e.g. specific speed nq, impeller width B2 or
efficiency η. This way SOM overcomes the problem of
visualizing multivariate data: input data are projected
onto a 2D grid (Figure 6).
Another advantage of the SOM is related to its intrinsic
interpolation capability. There might exist regions of
unexplored zones, the performance of the impeller is not
yet predicted by CFD. This is reflected in SOMs by empty
hexagons separating others that are filled up by different
families of designs. When this happens, it is reasonable to
look at the prototype vector of the empty unit as kind of
forecast of a design family that have still to be realized,
and that represent a reasonable interpolation of the ones
that are available. The benefit of the SOM is that, apart
from the input variables characterizing such design
families, also a complete forecast of the performances is
immediately available. This predictive use of the SOM is
really powerful when handling designs that are described
by a high number of parameters (inputs and outputs) so
that any other interpolations approach, like Response
Surface Modeling, becomes heavy to implement.
For the pump impellers described here, a unique SOM is
trained on the existing database and used to forecast new
design families able to provide certain performances.
Self-Organizing Map
Any existing impeller design is described through a multidimensional vector, where each component represents a
Impeller design and multi variate analysis
defining parameter (input) or a performance index
The dimensionless values for the main parameters and the
(output).
design objectives efficiency and suction capability (η,
The Self-Organizing Map (SOM) is an unsupervised Neural
nSS,bep, nSS,max) are selected as input for the training
Network algorithm capable to group and classify such
already available impeller designs in a two-dimensional
(classification) of the SOM. Within this test case, the
grid space. Each node of this grid is called “Unit” and it
results of six different impeller optimizations with three
groups (includes) vectors (impeller designs)
that are similar with respect to all their
parameters
(inputs
and
outputs)
simultaneously.
SOM preserves the topology of the data, so
that similar data items will be mapped to
nearby units on the map. To do so, units are
hexagonal-shaped, and hence each unit has 6
neighbors and is labeled by a “prototype
vector” that in fact represents all the vectors
included in the unit itself, as a kind of
average.
Fig. 6 - Left: SOM is the blue network that adapts to real data (red points) in a X-Y-Z space,
SOM lives in the multi-dimensional data note that some nodes are far from any real point, hence the related unit will be empty.
space, but its visualization capabilities are Centre: the same SOM in its 2D conventional representation: each of the nodes is a hexagonal
unit. Right: each unit is colored with respect to the X-value of its prototype vector, and the
built on the top of its representation in the square on its center represents the number of real design enclosed in the unit (see the empty
grid space. Each of the hexagons becomes a units).
Fig. 5 - Correlation between dimensional and non dimensional values
back from dimensionless
to
dimensional
parameters.
A
new
impeller is then generated
with the conventional
design tools and its
performance is checked by
CFD.
Fig. 7 - Specific speed (nq) in the SOM with distribution of existing
designs
Fig. 8 - Selected designs in the SOM (Color: specific
speed)
different specific speeds between nq13 and nq60 are used
as data basis. Goal of this study is to develop new
impellers in this range with high suction capability and
high efficiency for four different specific speeds (nq16,
nq24, nq30, nq47) under the assumption that for each nq
both operating point and impeller diameter D2 are given
and the shaft diameter is pre-defined from mechanical
calculations.
Figure 7 illustrates the trained SOM of the specific speed
ranging from nq13 (blue) to nq60 (red). The squares
describe the density of input parameters available. The
larger the square the more data exists, no square signifies
that parameter values are based on pure interpolation.
The selection of the new impellers is undertaken in
regions with purely interpolated data (Figure 8). For each
new impeller, existing designs with a similar nq in the SOM
table are compared. This is necessary as three objectives
need to be fulfilled, and the SOM designs might only
achieve one.
The advantage of this technique is the access to every
single parameter defining the impeller geometry. With an
amount of over 50 parameters, the entire meridional
impeller contour and the blade shape are approximated by
the SOM. This method allows a complete impeller design
within a few minutes just by giving the operating point
and selecting an appropriate outer diameter D2. The
impeller parameters are taken from the SOM and converted
Table 1 - Comparison of coefficients of obtained and predicted objectives for the
selected designs
Table
1
shows
a
comparison
of
the
performances obtained by
CFD and predicted by SOM
for the selected nq. A
coefficient is defined
with:
objectiveCFD / objectiveSOM ,
describing the ratio of the CFD result to the prediction of
the objective by the SOM. A value equal to one signifies
an error of zero; the CFD performance matches the
predicted one. For a coefficient smaller than one, the
performance is over predicted, if it is larger than one, the
design is under predicted by the SOM.
nq24
The first impeller modeled with the SOM is nq24. Therefore
the best possible solution in compliance with the specific
speed and the design goals is selected. CFD calculations
are performed according the CFD in the optimization
process. The results are excellent, both efficiency and
suction performance are better than predicted by the SOM.
nq16
For the second impeller (nq16) two different designs are
selected from the SOM table, one with high efficiency
predicted and a second with a lower efficiency but a
better expected suction capability. The impeller with high
efficiency reaches almost the suction capability at bep
while the impeller with the lower efficiency exceeds the
suction capability. Both impellers outperform the
expected suction capability at the maximum operating
point efficiency.
nq30
For the impeller nq30 two different interpolated designs
are selected from the SOM table, differing in suction
capability at maximum operating point. After
calculating performances of the interpolated designs,
the aspired suction capability at overload is not
achieved, the other targets are outperformed. For this
reason two more designs from the SOM table are
selected, now with lower efficiency than the previous
designs. With the lower efficiency target, the suction
capability is reached for both operating points. This
proves the conflicting design targets efficiency and
suction capability.
Fig. 9 - Efficiency (red = high, blue = low)
Fig. 10 - suction capability at bep (based on σ,
blue = good, red=bad)
nq47
Two designs from the SOM table are selected. The second
design with the higher suction capability target at bep
misses the required suction capability at maximum
operating point. Even if the first design does not fulfill
the requirements at bep, the deviation from the target
value is only small.
Summary for all designs
For all designs, the calculated efficiency is higher than
SOM predicted. The suction capability misses the
requirements for some designs because of contradicting
objectives. In these cases it is possible to select new
designs from the SOM with compromises in efficiency but
achieving the required suction capability.
Figures 9-11 present the objectives efficiency, suction
capability at bep and max OP. It can be clearly seen that
efficiency and suction performance pattern are completely
different. This discrepancy makes it difficult to fulfill all
three objectives and either a compromise is required or
one objective has to be prioritized.
Conclusions
The article describes a novel methodology to design
impellers starting from the well assessed knowledge at
Sulzer Pumps
Sulzer Pumps is one of the world's leading centrifugal
pump manufacturers. Intensive research and development
in fluid dynamics, process-oriented products and special
materials as well as reliable service helps Sulzer Pumps
maintain its leading positions in its key markets. Its
customers come from the oil and gas, hydrocarbon
processing, power generation and pulp and paper sectors
as well as from water distribution and treatment and
other general industries. The products are internationally
reputed for their technical excellence.
www.sulzerpumps.com
9
Fig. 11 - suction capability at max OP (based on σ,
blue = good, red=bad)
Sulzer Pumps. The concept has proven to provide the
designer a new and effective tool to speed up the design
process of the pumps core part - the impeller.
Self-Organizing Maps (SOM) have been trained on the
already available impeller designs and corresponding
performance indicates: such a SOM embeds the so far
available pump designer knowledge, and provides a
complete interpolation in regions in which designs are
still missing. Each input or output variable of the impeller
design can be represented through a conventional twodimensional SOM map. This allows the use of SOM as an
extremely powerful tool to suggest new designs in regions
in which the design space has not yet been explored to
forecast their performances. In fact, the methodology
allows a new and complete impeller design in some
minutes, just assigning a few parameters, as the operating
point and the outer diameter. Any new design proposed by
the SOM can be validated through high-fidelity fluid
dynamic simulations (CFD) and then be used as starting
point for further refinements by directly linking the CFD
model to a modeFRONTIER optimizer, [2].
References
[1] Gülich J.: "Centrifugal Pumps", Springer, 2010
[2] Krüger S., Maurer W.: "How to use modeFRONTIER
within the daily hydraulic design process: Sulzer
Pumps’ experiences with automated impeller design",
modeFRONTIER 2008 Users’Meeting, Trieste, 14th-15th
October 2008
Wolfgang Maurer, Susanne Krueger
Sulzer Pumps, Winterthur, Switzerland
Luca Fuligno
EnginSoft SpA, Trento, Italy
Francesco Linares
EnginSoft GmbH, Frankfurt am Main, Germany
Analisi di un meccanismo link-drive per
presse con tecnologia multibody in
ANSYS
Analysis of a link drive mechanism for presses using ANSYS
MBD multibody technology
This paper presents a test case in which the tool “Rigid
Dynamics” of ANSYS Workbench 13 is used to investigate the
kinematics and the dynamics of a link drive mechanism
equipping a deep drawing press.
The device is first analyzed by developing the kinematic motion
equations. This step highlights the difficulty which arises when
we have to manually manipulate the equations of a complex
multibody system.
Then, a parameterized multibody model of the link drive is built
in ANSYS. This approach is much more straightforward and
allows the user to understand the mechanism’s behavior in a
shorter time. In addition, the software makes it possible to
watch the working mechanism animation at the end of the
solution.
The multibody model returns information about the dynamics,
which is useful for structural design purposes. Moreover, thanks
to the easy parameter management in ANSYS, we can
automatically investigate and compare multiple alternatives of
the same mechanism.
Questo articolo presenta un test case significativo nel quale attraverso una “Rigid Dynamics” di ANSYS Workbench 13 vengono efficacemente analizzate la cinematica e la dinamica di una
pressa meccanica per imbutitura profonda.
L’imbutitura è un processo di formatura a freddo attraverso il
quale una lamiera metallica viene trasformata in un oggetto cavo, con buone caratteristiche dimensionali e di finitura. Nello
schema tradizionale, l’imbutitura si realizza attraverso un pun-
zone che spinge la lamiera, eventualmente fissata con un premilamiera, all'interno di una matrice. Il processo è intrinsecamente delicato perché deve indurre nel materiale elevate deformazioni plastiche, senza raggiungere la condizione di rottura.
La qualità del prodotto finale è fortemente influenzata dai parametri di processo, tra i quali spicca per importanza la velocità di discesa del punzone nel tratto di corsa in cui lavora la lamiera.
Idealmente, la velocità del punzone dovrebbe essere bassa, per
realizzare una deformazione graduale del materiale, e costante,
per evitare la formazione di pieghe e striature superficiali.
In una pressa meccanica con tradizionale schema slider crank,
la riduzione della velocità del punzone è ottenibile solo aumentando il tempo ciclo, con ovvie conseguenze negative sulla produttività dell’impianto. Pertanto, se si vogliono ottenere
buone performance di processo senza penalizzare la produzione, è opportuno predisporre un meccanismo più raffinato, che
consenta maggiori libertà nella gestione della velocità del punzone. Una soluzione è il meccanismo link drive illustrato, già
utilizzato da alcuni produttori di presse. La Figura 1 confronta
le curve di velocità del punzone per una pressa tradizionale e
una pressa link Drive di pari dimensioni (con la stessa corsa
massima e lo stesso tempo ciclo).
La velocità di discesa del punzone, per la pressa link drive, presenta un tratto con andamento regolare a velocità quasi costante. Inoltre, grazie al maggior numero di membri, questo
meccanismo è molto versatile: variando le dimensioni del meccanismo si possono ottenere diverse curve di velocità. Risulta,
pertanto, evidente che il link drive presenta caratteristiche e
prestazioni molto più vantaggiose dello schema tradizionale.
Studio analitico del meccanismo link drive
Il paragrafo precedente ha messo in luce l’importanza della velocità di discesa del punzone nella messa a punto del processo
di imbutitura. Pertanto, è opportuno focalizzare l’attenzione
sull’analisi cinematica del meccanismo link drive, che permette
di comprendere come il meccanismo trasformi la rotazione del
motore elettrico nella traslazione a velocità variabile del punzone.
Fig. 1 – confronto tra pressa “Slider–Crank”e “link drive”:
velocità del punzone e zona di lavoro
Gli approcci per condurre uno studio cinematico sono diversi.
Per un meccanismo relativamente semplice come il link drive,
è possibile, seppure con qualche difficoltà, derivare analiticamente le equazioni del moto. Lo schema cinematico cui si farà
riferimento è riportato in Figura 2.
11
Simulazione multibody del meccanismo link drive
Una valida alternativa per studiare meccanismi in modo più veloce e con minor rischio di errore è la simulazione tramite codice multibody. ANSYS Workbench 13, attraverso il modulo
“Rigid Dynamics”, consente di creare e gestire modelli
multibody a corpi rigidi. L’utilizzo di questo strumento, permette, inoltre, di integrare i risultati dell’analisi cinematica con
tutte le grandezze dinamiche fondamentali per la progettazione strutturale del dispositivo.
ANSYS Workbench 13 consente di gestire in modo parametrico
qualsiasi modello di calcolo. Con riferimento all’analisi
multibody del link drive, la parametrizzazione permette di simulare varie alternative del meccanismo, consentendo la scelta di quella più adatta alle esigenze.
Fig. 2 – schema cinematico della pressa link drive
I vettori L1, L3, L4, L5 e L6 rappresentano i membri mobili del
meccanismo, il vettore L2 rappresenta il telaio e il vettore s rappresenta la posizione del punzone (misurata da un riferimento
arbitrario). Lo studio analitico della cinematica inizia con la
scrittura delle equazioni di chiusura in forma vettoriale:
Ciascun vettore può essere formalmente descritto nella forma
L= L cos (φ), dove L è la lunghezza e φ è l’angolo di inclinazione. Sostituendo nelle precedenti e manipolando opportunamente è possibile esprimere la posizione s del punzone in funzione dell’angolo φ4 di rotazione dell’eccentrico (variabile indipendente del problema). Successivamente, si ricavano per derivazione rispetto al tempo la velocità v e l’accelerazione a. In
sintesi, l’analisi cinematica mediante approccio analitico restituisce tre equazioni nella forma:
Nella fase di pre-processing avviene l’assemblaggio del modello multibody. Le geometrie dei corpi possono provenire da CAD
esterni oppure possono essere create direttamente all’interno
di Design Modeler. Per questa applicazione abbiamo provveduto a creare integralmente la pressa ed il meccanismo, parametrizzando le grandezze di cui andremo ad analizzare gli effetti.
Sono quindi state scelte e create le connessioni tra i corpi
(Figura 3).
I revolute joint consentono la rotazione relativa tra i membri
connessi, mentre i general joint lasciano liberi i gradi di libertà scelti esplicitamente dall’utente.
Per consentire la soluzione di un modello multibody a corpi rigidi, i vincoli, inseriti sottoforma di connessioni, non devono
essere ridondanti. ANSYS mette a disposizione lo strumento
“Redundancy Analysis” che permette di individuare automaticamente la presenza di vincoli in eccesso e che fornisce indi-
Queste espressioni hanno una struttura molto articolata e pertanto ne omettiamo la scrittura estesa. Si noti che i risultati
dipendono dalla legge di moto assegnata al movente e dai parametri dimensionali del meccanismo.
Benché l’approccio analitico consenta di pervenire ai risultati
cinematici in tempi accettabili, va precisato che la manipolazione di equazioni con questo livello di complessità è una operazione alquanto delicata: se non si dispone di strumenti per la
manipolazione simbolica, il rischio di errore è decisamente elevato.
Fig. 2 – vista 3D dell’assieme e schema delle connessioni
Confronto di 3 configurazioni del meccanismo link drive
A titolo di esempio, proponiamo lo studio comparativo della risposta cinematica restituita dal meccanismo link drive modificando la coordinata orizzontale della cerniera di collegamento
della biella L1 al telaio (Figura 2 e Figura 4).
Nello specifico, abbiamo ipotizzato di passare da un valore di
1400 mm a 1100 mm, con un valore intermedio di 1250 mm.
Le tre analisi sono condotte semplicemente modificando il parametro corrispondente nell’interfaccia utente. ANSYS MBD aggiorna automaticamente le geometrie e ripete la simulazione
multibody.
Fig. 4 – modelli di pressa ottenuti tramite parametrizzazione
cazione di quali modifiche si debbono apportare per rendere il
modello consistente.
Il meccanismo virtuale viene azionato applicando una legge di
moto all’albero dell’eccentrico. ANSYS consente di assegnare a
qualsiasi connessione sia leggi di moto, sia azioni dinamiche.
In entrambi i casi, le funzioni sono gestibili in forma tabulata
o tramite espressioni analitiche. Nel caso del meccanismo link
drive, abbiamo imposto al movente una velocità di rotazione
costante.
L’analisi multibody comporta l’integrazione delle equazioni del
moto che il software ha sviluppato automaticamente durante
l’assemblaggio del modello. ANSYS dispone di due integratori,
con diverse opzioni per la gestione del passo, della convergenza e della qualità della soluzione.
Nella fase di post-processing ANSYS Workbench permette di
estrarre numerosi risultati dai corpi e dalle connessioni. Le
grandezze disponibili per i corpi sono di natura cinematica (posizione, velocità, accelerazione), mentre per le connessioni
possiamo diagrammare le grandezze cinematiche dei gradi di libertà consentiti e le reazioni vincolari dei gradi di libertà annullati dal joint.
Ad esempio, su un “revolute joint” possiamo leggere angolo,
velocità ed accelerazione angolare lungo l’asse di rivoluzione,
e, in aggiunta, possiamo estrarre forze radiali, forze assiali e
momenti trasversali che i corpi si scambiano mutuamente.
Fig. 5 – confronto della velocità del punzone per i tre modelli di pressa
La Figura 5 illustra gli effetti del parametro scelto sulla velocità del punzone. Lo zoom mette in particolare evidenza la comparsa del tratto a velocità quasi costante, passando dalla pressa A alla pressa C. Pertanto, se l’obiettivo è quello di usare la
pressa per un processo di imbutitura, la soluzione C è la migliore. Naturalmente, sfruttando la parametrizzazione del modello,
è possibile individuare configurazioni con prestazioni ulteriormente migliorate.
Per maggiori informazioni:
Fabiano Maggio - EnginSoft
[email protected]
L’esempio del meccanismo link drive solleva una serie di
problematiche tipiche della modellazione multibody. Infatti,
l’utente deve scegliere con cura numero e tipologia di vincoli
se non vuole pervenire a risultati incompleti o addirittura
errati. L’utilizzo di strumenti come “ANSYS Transient
Structurla MBD” presuppone che l’utente possieda adeguate
nozioni di meccanica applicata e calcolo numerico che gli
consentano di tradurre correttamente un sistema fisico in un
modello virtuale. La schematizzazione può avvenire in modo
più o meno raffinato, con conseguenze dirette sull’efficacia
della simulazione. È compito del modellista scegliere
dimensione, grado di complessità e dettagli del modello che
vuole creare, considerando simultaneamente obiettivi da
raggiungere, onere computazionale e tempo a disposizione.
Il miglior modello non è quello più dettagliato, ma quello
che risponde in modo più veloce ed esauriente alle esigenze.
Questa regola, che vale in generale per tutte le dimensioni
del CAE, assume un ruolo decisivo per la simulazione
multibody.
EnginSoft propone un corso di modellistica multibody della
durata di 2 giorni a tutti i progettisti che affrontano
quotidianamente problemi di cinematica e dinamica. Il corso
è pensato e strutturato in modo da trasferire in breve tempo
le conoscenze che servono a formulare consapevolmente le
principali scelte di modellazione multibody. Il corso verrà
tenuto dal prof. Roberto Lot dell’Università di Padova in
collaborazione con l’ing. Fabiano Maggio di EnginSoft.
Per informazioni sui contenuti consultare il sito del
consorzio TCN www.consorziotcn.it
Per iscrizioni e informazioni generali consultare la sig.ra
Mirella Prestini della segreteria del consorzio. E-mail:
[email protected] Tel: 035 368711
13
Ottimizzazione termofluidodinamica di
un forno da cucina Indesit
Indesit Company è tra i leader in
Europa nella produzione e commercializzazione di grandi elettrodomestici:
lavabiancheria, asciugabiancheria, lavastoviglie, frigoriferi, congelatori,
cucine, cappe, piani di cottura e forni.
Proprio su quest’ultimo prodotto, il
forno da cucina, si è recentemente
concentrata un fase di sviluppo volta a
migliorarne efficienza in termini di
consumi e di uniformità di cottura.
Lavorando già da tempo con strumenti di modellazione numerica (nello
specifico ANSYS ICEM CFD e ANSYS CFX) Fig. 1
per coadiuvare le prove sperimentali,
Indesit Company ha deciso di utilizzare tali strumenti per tutta
la fase di ottimizzazione della termodinamica interna del forno,
avvalendosi del software di ottimizzazione modeFRONTIER e della collaborazione dei tecnici della EnginSoft S.p.A.
A valle di studi sperimentali e considerazioni basate su know
how interno, si è pensato che, per migliorare le prestazioni del
forno dal punto di vista energetico e funzionale, l’attenzione
maggiore doveva essere posta sulla paratia forata che si trova tra
la ventola e la zona di cottura. Il lavoro presentato, è quindi
quello dell’ottimizzazione geometrica di tale paratia, alla ricerca
della configurazione tale da avere minori consumi ed una maggiore uniformità di temperatura nella muffola.
lativi alla dimensione degli elementi
della griglia di calcolo, sia a livello
globale che locale. Per tutte le configurazioni analizzate, 3 strati di prismi
sono stati estrusi su tutte le pareti del
dominio di calcolo. Le griglie di calcolo che tipicamente si possono ottenere con questa impostazione constano
di circa due milioni di elementi tetraedrici ed un milione di prismi. È chiaro
tuttavia che il numero di elementi è
leggermente diverso per ogni configurazione, essendo la geometria parametricamente variata per ogni design.
L’attività sul modello baseline, oltre
che rappresentare il riferimento per quantificare il margine e la
direzione del miglioramento nella fase di ottimizzazione, è servita anche per la fase di taratura, indispensabile in attività di
questa portata per determinare il miglior compromesso tra numero di elementi, qualità degli stessi e numerica più efficace all’ottenimento di risultati affidabili del calcolo CFD.
Variabili di Input ed Output
modeFRONTIER è un ottimizzatore multi disciplinare e multi
obiettivo. L’esperienza che vanta EnginSoft nell’utilizzo di questo strumento accoppiato a software di analisi numerica, ha consentito la messa a punto di un flusso logico di macro-operazioni che hanno portato ad una vera e propria “customizzazione”
per il problema qui illustrato (ottimizzazione forno).
I parametri geometrici di ingresso sono stati in tutto sedici. Essi
hanno permesso di controllare dimensione, distribuzione e numero di fori sui quattro bordi della paratia. Lo spazio delle possibili configurazioni è stato delimitato in tre modi: dai valori minimi e massimi che ciascuna variabile di input doveva rispettare, da vincoli di costruzione, e da vincoli geometrici che evitassero geometrie degeneri.
Modellazione
Si è partiti dalla modellazione di tutto il “volume bagnato” del
forno nella configurazione baseline di partenza. Il forno, in questa configurazione, presenta anche una leccarda nella parte inferiore della zona di cottura. Sfruttando il fatto che la parte geometrica soggetta a modifica parametrica è la sola paratia, si è
pensato di dividere il volume in due parti con un piano che separi il dominio di calcolo in prossimità della paratia. In questo
modo, la parte di modello a valle della paratia, comprendente
Discorso un po’ più dettagliato meritano le variabili di output. A
anche tutta la leccarda, rimane invariata, e viene perciò prepamonte del lavoro di ottimizzazione è stata valutata molto attenrata (geometria + griglia di calcolo) una sola volta. L’altra parte
tamente la modellazione delle variabili in uscita. Esse infatti dedel modello, è a sua volta suddivisa in un volume che rimane invono rappresentare un indice sia dell’efficienza del forno in tervariato, il dominio rotante con la ventola, e tutto il resto, commini di uniformità della temperatura che del suo consumo di
prendente fra gli altri la paratia, la cui geometria e griglia di calcolo sono state parametrizzate per poter essere rigenerate automaticamente di volta in volta sulla base delle scelte operate dal’ottimizzatore.
Il software utilizzato per le modifiche geometriche e la generazione della griglia di calcolo è stato ANSYS ICEM CFD.
Mettendo a punto una sequenza di istruzioni opportune, ICEM
modifica la geometria della paratia e genera la griglia del volume ottenuto. In questo insieme di istruzioni (script) sono
presenti oltre a tutti i parametri geometrici, anche quelli re- Fig. 2
energia. Si è deciso di scegliere
come grandezza per l’uniformità
di temperatura, il suo scarto quadratico medio (RMS di T) misurato su una nuvola di punti situata
“ad hoc” nella zona di cottura,
mentre per la potenza elettrica
necessaria si è optato per la portata d’aria ricircolante all’interno
della muffola. Con queste assunzioni, gli obiettivi implementati
in modeFRONTIER diventano perciò la ricerca di un design che
renda minimo il valore dello scarto quadratico medio delle temperature sulla nuvola di punti garantendo allo stesso tempo una
portata d’aria superiore ad un va- Fig. 3
lore limite precedentemente stabilito come limite inferiore.
Il processo logico che lega tutti i passaggi è il seguente:
• Partendo dal file replay.rpl che modeFRONTIER ha aggiornato con i valori delle variabili di ingresso, lo script, eseguito
in batch da ICEM, si occupa di modificare la paratia con i
fori, copiare il resto della geometria che resta immutata e
generare la griglia di calcolo.
• Terminata questa prima fase, la griglia di calcolo generata
viene caricata assieme a quella che resta inalterata nel preprocessor di CFX. Al modello così aggiornato viene quindi
applicato il setup fisico e numerico dell’analisi cfd, scritto il
file di lancio e lanciato il run, specificando eventualmente se
il calcolo deve essere eseguito in modalità parallela. Anche
questa fase è interamente eseguita in modalità batch da tutti i software coinvolti.
• Finita l’analisi, sempre in batch, un altro script del post-processore di CFX, calcola le grandezza di output dal file di
risultati, concludendo così l’iterazione per il singolo design
Doe e Ottimizzazione
Il DOE (Design Of Experiment) di partenza è stato realizzato mediante l’algoritmo RANDOM tra i più adatti per un’ottimizzazione mono-obiettivo. In effetti anche se gli output sono due, solo la minimizzazione dello scarto quadratico medio della temperatura è un vero e proprio obiettivo, dato che il controllo del valore di portata d’aria smaltita dalla ventola sia sempre superiore
ad un valore minimo è considerato come un vincolo del problema. Il numero di design iniziale, dipendente anche dal tipo di
algoritmo scelto per l’ottimizzazione, è in questo caso calcolato
come la somma dei parametri di ingresso più uno, come richiesto dall’algoritmo di ottimizzazione utilizzato.
A seguito della campagna di analisi sui risultati del DOE di partenza, è iniziata la fase di ottimizzazione, mediante l’utilizzo
dell’SIMPLEX. Il numero di design simulati in questa fase, utili
all’ottenimento di una buona convergenza dell’algoritmo stesso,
è stato di 107.
Ottenuto il design “ottimo”, sfruttando le potenzialità di postprocessing e statistica presenti all’interno di modeFRONTIER è
stato possibile estrarre dalla considerevole
mole di dati resisi disponibili, delle informazioni importanti per capire il legame tra le
varibili di input e tra ciascuna di esse e
l’obiettivo. Più in generale, questa fase consente di raccogliere delle preziose informazioni per capire più approfonditamente il
problema studiato, soprattutto laddove esso
dipenda da diversi input e output anche fra
loro in forte contrasto, tipicamente con
comportamento non lineare.
Strumenti quali matrici di correlazione, grafici a coordinate parallele, filtri, bubble multidimensionali, hanno consentito di stabilire quale sia il peso dei singoli ingressi sui risultati, e quale sia il migliore intervallo di
utilizzo tra i valori ammissibili, per ogni variabile.
Infine, conoscendo come ogni variabile influisce sul risultato finale, partendo dal miglior design sono state implementate modifiche aggiuntive, che, integrando quelle previste dallo spazio
parametrico sopra illustrato, hanno portato ad un ulteriore miglioramento delle performance del forno.
Dall’attività nel suo complesso, ne è scaturita una profonda conoscenza del fenomeno fisico, delle relazioni fra le variabili, con
soddisfacenti riscontri sperimentali.
Risultati e Conclusioni
Grazie alle simulazioni numeriche e all’esperienza dei tecnici
Indesit nell’indirizzare decisioni e assunzioni da prendere, le
prestazioni del forno da cucina sono migliorate nell’ordine del
20% sullo scarto quadratico medio rispetto alla configurazione
iniziale.
Le prove sperimentali sul miglior design hanno confermato i risultati numerici ed un risparmio energetico dovuto ad una portata smaltita dalla ventola superiore a quella del design di partenza.
Gianluca Mattogno, Indesit - [email protected]
Fabio Damiani, EnginSoft - [email protected]
Fig. 3
15
Combined 1D & 3D CFD Approach for
GT Ventilation System analysis
The Gas Turbine ventilation system is designed to supply
the necessary amount of air for cooling and to prevent the
accumulation of hazardous gases in the enclosure by
maintaining a slight over-pressure. The classical GE
approach to studying ventilation system operating
conditions consists of modeling the whole system as a
series of discrete losses, where the ASHRAE duct-fitting
database provides the corresponding pressure loss
coefficients. The system is solved by means of a onedimensional flow simulation tool (Flowmaster).
The goal of this work was to improve the critical points
that affect the above-mentioned procedure, such as
modeling of complex fittings and bend interactions. For
this purpose, dedicated CFD analyses were performed to
characterize the loss coefficient for splitting and bend
interactions at different operating conditions (split
percentage and inlet flow rate) for two different
ventilation systems. The resulting loss coefficient curves
have been implemented within the corresponding onedimensional Flowmaster models. Finally, to characterize
off-design conditions, a variable Heat Rejection model
(obtained from previous CFD analyses) and real fan curves
were used.
This new approach produces more accurate results, as
confirmed by the close agreement with experimental
measurements. Among the benefits of using this new
approach is the ability to characterize the flow behavior
of complex fittings. This would be useful in the event of
a fitting redesign or for noise reduction analyses.
Current GE approach to studying
Gas Turbine Ventilation Systems
A ventilation system must provide a continuous source of
cooling air over the entire Gas Turbine operation range in
order to:
• maintain a uniform and constant airflow through the
flange-to-flange Gas Turbine at all ambient conditions;
• remove heat and maintain the air temperature in the
compartment below the operating limit. (The
operating limit is set according to the temperature
rating of the components located in the
compartment);
• eliminate stagnation zones and prevent the
accumulation of hazardous gases;
• prevent the ingress of dust and sand in gas turbines
located in regions prone to sandstorm conditions by
means of proper compartment pressurization.
Specific Design Practices provide a general description,
acceptance limits and design criteria that a ventilation
system must meet for Oil & Gas applications (e.g.,
enclosure design temperature ranges, design pressure
ranges, purging ranges, etc.).
As mentioned, the current GE approach to studying GT
ventilation systems consists of modeling the whole system
as a series of “blocks”. Each block represents a source of
pressure loss (concentrated loss) due to changes in shape
(e.g., elbow, transition, etc.), flow direction or the
presence of physical obstacles within the system. The
ASHRAE duct-fitting database provides the corresponding
pressure loss coefficients.
Following the net balancing by means of a onedimensional flow tool (Flowmaster), the system is
characterized in terms of velocities, pressures, and flow
rate split.
Critical points for this approach are the modeling of
complex fittings and bend interactions. In order to
improve the current Ventilation System calculation
procedure, dedicated CFD analyses were performed for
these critical points. A combined 1D & 3D CFD approach
was adopted to study two different GE Ventilation
Systems, called for simplicity System A and System B.
Numerical calculations for System A
The current System A Flowmaster network, modeled as a
series of discrete losses, is shown in Figure 1. The
Fig. 1 - System A Flowmaster model based on discrete losses.
enclosure is modeled as two heaters and the fan as two
3
flow sources with a flow rate of 65000 m /h, estimated by
using the enthalpy balance equation:
K12 (GT Compartment)
K13 Load Compartment
ASHRAE Database
0.4
0.71
modified ASHRAE model
(experience based)
1.15
1.5
CFD
0.4-0.6
2.28
Table 1: Loss coefficients used for standard calculations, System A.
were:
= mass air flow [Kg/s],
= enclosure heat rejection [W]
= specifiwec heat at constant pressure [J/Kg °C]
= maximum allowable outlet air temperature [°C]
= max ambient temperature [°C]
In order to develop a more suitable model (taking into
account interactions, 3D characteristics of the fluid, etc.),
dedicated ANSYS FLUENT CFD analyses were performed. In
particular, a critical point for the discrete losses modeling
is the flow split into the Load Compartment and the Gas
Turbine Compartment (see Figure 2).
Fig. 2 - Analyzed split (left) and Load Compartment final section (right),
System A
defined in (2), as a function of the flow rate split (see
Figure 3).
Subsequently, these coefficients were implemented within
the corresponding one-dimensional Flowmaster model.
A comparison between the loss coefficients obtained
using CFD and those coefficients used for standard
calculations is summarized in Table 1.
Finally, to better simulate the ventilation system a bend
interaction analysis was performed on the Load
Compartment final section, which is highlighted in Figure
2 (for System B the geometry of this section is the same).
The total loss coefficient as a function of the inlet
velocity is shown in Figure 4. The loss coefficient
decreases as the inlet flow velocity increases, and a good
agreement with the ASHRAE database value was found for
a velocity of about 5m/s. For higher velocity values the
difference between the two curves (CFD and ASHRAE)
starts to be significant. Again, the loss coefficient curve
obtained was implemented within the new model.
The fan, previously modeled as two flow sources, was
replaced by the “FAN” element with the corresponding real
operating curve.
The final System A Flowmaster model including the main
differences from the standard approach is shown in Figure
5.
It is useful to define the coefficients K12 and K13 as:
;
where:
P01 = inlet total pressure
P02 = GT Compartment total pressure
P03 = Load Compartment total pressure
V2 = GT Compartment mean velocity
V3 = Load Compartment mean velocity
For the characterization of the flow
split at different operating points,
two test campaigns were performed.
In both cases the inlet flow rate was
3
3
fixed (65000 m /h and 130000 m /h,
respectively) and, for each of these, a
variable split percentage between the
GT and Load compartments was used.
These analyses provided K12 and K13,
The results obtained with the new model were compared
with the results obtained by the ADV (Air Ducts and
Ventilation) department using a model based on the
ASHRAE loss coefficient with appropriate corrections
based on experience and with the results obtained with a
pure ASHRAE model (see Table 2). The reliability of each
approach was evaluated through comparison with
experimental data.
Fig. 3 - K12 and K13 as a function of flow rate split for two different inlet flow rates, System A.
17
lower than 5%). On the contrary, the pure ASHRAE model
produced an error of 18%.
Numerical calculations for System B
Also for the System B split, several tests were performed
to determine the split loss coefficients for different
operating conditions. Figure 7 shows K12 and K13 as a
function of the split flow rate percentage between the GT
and Load compartments for an inlet flow rate equal to
3
70000 m /h (design flow rate). As one can see, both
curves follow a linear trend.
Fig. 4 - Loss coefficient curve for Bend Interaction.
Similar to the System A model, the new
System B Flowmaster model contains the
loss coefficient curves obtained from CFD
analyses (including the bend interaction
curve) and the real fan operating curve.
Finally, in order to better simulate the
heat removal, the heat rejection was
modeled as a function of the mass flow
rate, in accordance with recent studies
performed by the SYS-OPT (System
Optimization) department, that is:
where:
HR = heat rejection
HR0 = reference heat rejection
= mass flow rate
0 = reference mass flow rate
n = reference exponent
Fig. 5 - New System A Flowmaster model.
Table 2 summarizes the results obtained for the enclosure
pressure. Using the new approach we got a favorable level
of approximation with respect to the measured value
(error equal to 7%). The other two approaches yielded
errors higher than 25%.
The final System B Flowmaster model is shown in Figure 8.
Figure 9 shows the GT and Load Compartment velocity
obtained with the STD model (previous calculations) and
the new model for dirty and clean filter house conditions.
Figure 6 shows for each model the load compartment
velocity and the corresponding error from the measured
value at clean filter house conditions. The measured mean
velocity is 12.47 m/s.
Both the new model and the modified ASHRAE model
(experience-based) led to a high level of agreement (error
Enclosure
Pressure[mmH2O]
Measured
value[mmH2O]
Error[%]
Discrete loss model
(ASHRAE)
54.40
43.0
26.5
Discrete loss model
(Experience based)
54.86
43.0
27.6
New model
(Flowmaster+CFD)
40.00
43.0
-7.0
Table 2: Enclosure pressure, clean filter house conditions, System A.
Fig. 6 - Load compartment velocity, clean filter house conditions, System A.
In both cases, the load
compartment velocity obtained
with the new approach is
significantly higher than the old
value (+49%). In particular, for
the new approach, we got a split
of 89-11% compared to a value of
92.7-7.3%
obtained
from
previous
calculations.
Considering that the target flow
rate is 90-10%, the new approach
again provides more accurate
results.
Fig. 7 - K12 and K12 as a function of flow rate split, System B.
No significant variations between
the two approaches in terms of
enclosure
pressure
and
temperature were found.
Conclusions
In this work, a combined 1D and
3D numerical approach was
adopted to study two GE
ventilation
systems.
This
approach, compared to the
current
one-dimensional
approach,
improves
the
simulation of the actual operating
conditions in terms of inlet flow
rate, duct velocity and enclosure Fig. 8 - New System B Flowmaster model.
pressure, as confirmed by the
References
close agreement with experimental
[1] Miller, D.S.: Internal Flow Systems; 2nd Edition, Miller
measurements.
Innovations, 2008
Among the benefits of using this new approach is the
[2] Idelchik I.E.: Handbook of hydraulic resistance, 3rd
ability to characterize the flow behavior of complex
Edition, CRC Begell House, 1994
fittings. This would be useful to support the redesign of
[3] ASHRAE Duct Fitting Database, Version 2.5.0. ASHRAE
fittings or for noise reduction analyses.
About GE Oil & Gas
GE Oil & Gas (www.ge.com/oilandgas) is a world leader
in advanced technology equipment and services for all
segments of the oil and gas industry, from drilling and
production, LNG, pipelines and storage, to industrial
power generation, refining and petrochemicals. We
also provide pipeline integrity solutions, including
inspection and data management, and design and
manufacture wire-line and drilling measurement
solutions for the oilfield services segment. As part of
our 'Innovation Now' customer focus and commitment,
GE Oil & Gas exploits technological innovation from
other GE businesses, such as Aviation and Healthcare,
to continuously improve oil and gas industry
performance and productivity. GE Oil & Gas employs
more than 12,000 people worldwide and operates in
over 100 countries.
L. Barbato, M. Blarasin, S. Rossin
GE Oil & Gas,
Via Felice Matteucci 2, Florence, Italy
Figure 9 - GT and Load compartment velocity for STD and New approach,
System B.
19
ANSYS WB and a review of the design
metrics in Piaggio: the case of the
motor shaft
I still can remember the time when, looking at a 3D CAD
model of an engine block, I would start thinking about the
best way to translate it into a PREP7 procedure. I would
come up with something to mesh, but the next time I
would have to start from scratch again. In those times,
beam representations in conjunction with SIFs were the
best way to go with crankshafts. Other components
required similar efforts.
Things evolved in a continuous fashion, but a
discontinuity came when ANSYS changed its face
completely with Workbench. At first I thought that
dealing with it would have been a dive into a bottomless
ocean, just like the first time I met a CONTA174. But I’ve
always been a fundamentalist when it comes to new CAE
techniques, so I tried to move to WB as quickly as I could
and to the maximum possible extent.
And my way of working radically changed: geometry
import and meshing issues sharply decreased, and past
models could be used as templates for new, similar
analyses. This last aspect evolved dramatically with the
introduction of WB projects, where bunches of
interconnected analyses form now real CAE procedures,
laid down with nearly no effort.
Such a case happened just a few weeks ago when I came
up against a crankshaft simulation.
I had to use WB both as stand-alone application and as
part of a CAE chain, including MBS and durability
analyses.
The simulations I had to perform required both linear and
nonlinear models, involving the simulation of neighboring
components, in addition to the crankshaft proper. WB
allowed me to quickly setup a baseline model: DM fixed a
few CAD issues and Mechanical Automatic Contact
detection feature greatly speeded up the assembly setup.
The CAD interface can sense CAD simplified
representations, allowing to perform partial CAD imports,
really useful when dealing with big CAD models.
Generating all the other models I needed from the
baseline one was really easy at a project level, duplicating
when a different topology was needed and linking when
only different load systems or different analysis types
were required.
That way, I could assess both the frictional load transfer
capability and the fatigue performance of the crankshaft
assembly.
For the former I used nonlinear models, exploiting the WB
contact features, whose default settings are much more
error-proof than navigating among all the keyoptions and
bodies included in an assembly, of the contact interfaces,
or the available postprocessing quantities, to name a few.
From a table you can jump to the relevant model element
with a simple click. So Worksheets prove to be a nice tool
to check what you’ve done.
The fatigue analyses required the computation of
load/stress transfer functions and of a Craig-Bampton
modal representation [1]. The latter was calculated by
means of a simple combination of rigid Remote
Displacement features and of a Commands object: no more
messing around with CERIGs, since WB did the job totally
in the background.
The results of the activity were not only fatigue safety
factors and stress distributions; besides them, and above
all, a neat trace of what I did has been left both at a
Project and System level, in the WB jargon. The next time
a similar component will have to be simulated, it will be
an update process, not a generation one. Opening the WB
project, the modeling procedure will be easily
recognizable.
real constants of the good old CONTA family. I could check
the functionality of friction couplings with both standard
and custom postprocessing quantities. The latter are
easily definable with the aid of another WB feature: the
Worksheets.
With them you have an overview of your modeling stages
in a neat tabular form. You can check the properties of the
In the past the CAE techniques had a hard time trying to
be simultaneously fast and accurate; that slowed their
integration into the development process of complex
systems. I think that WB has been one of the major
milestones in overcoming these problems, therefore
allowing the simulations to be perceived as standard and
required activities.
For more information:
Roberto Gonella - EnginSoft
[email protected]
[1] R.R. Craig, M.C.C. Bampton - Coupling of substructures
for dynamic analyses - AIAA Journal,vol. 6, n.7, 1968
21
EnginSoft
interviews Ing.
Paolo Nesti,
Piaggio Group
EnginSoft
intervista l’ing.
Paolo Nesti del
Gruppo Piaggio
ABOUT THE PIAGGIO GROUP
The Piaggio Group was founded in 1884 and nowadays is the European leader and one of the
major players worldwide in the sector of twowheeler vehicles. The Group is also a global leader in the development and manufacture of
commercial vehicles. The product range of the
Piaggio Group includes scooters, motorbikes and
motorcycles from 50 to 1,200 cc and the trademarks: Piaggio, Vespa, Gilera, Aprilia, Moto
Guzzi, Derbi, Scarabeo. In the light commercial
vehicle market, Piaggio is represented with its
three- and four-wheeler vehicles and the trademarks: Ape,
Porter and Quargo.
The Group’s head office is based in Pontedera (in the province of Pisa, Italy). Since 2003, it is managed by the industrial
holding Immsi S.p.A. Roberto Colaninno is the President and
Managing Director of the Piaggio Group.
The manufacturing plants are located in: Pontedera (Pisa),
Noale and Scorzè (Venice), Mandello del Lario (Lecco),
Martorelles (Barcelona, Spain), Baramati (India, in the
Maharashtra nation), and Vinh Phuc (Vietnam).
Furthermore, there is a joint venture in China (in Foshan, in
the province of Guangdong). In 2009, the Piaggio Group sold
607.700 vehicles worldwide: 410,300 two-wheeler vehicles
and 197.400 commercial vehicles. Motorcycle racing is a very important business for the Piaggio Group. Some Piaggio
models are well known for some world records: 95 world
championships won in different fields and more than 500 victories in different competitions. Among the most successful
brands is Aprilia. With its 45 global qualifications and 278
wins in the GP, Aprilia is the most successful brand in the history of the GP Motorcycle Racing in Italy and Europe.
IL GRUPPO PIAGGIO: PROFILO
Il Gruppo Piaggio, fondato nel 1884, è il più
grande costruttore europeo e uno dei principali player mondiali nel settore dei veicoli motorizzati a due ruote. È inoltre protagonista internazionale nel settore dei veicoli commerciali. La gamma di prodotti del Gruppo comprende scooter, moto e ciclomotori da 50 a 1.200cc
con i marchi Piaggio, Vespa, Gilera, Aprilia,
Moto Guzzi, Derbi, Scarabeo, e veicoli commerciali leggeri a tre e quattro ruote con le gamme Ape, Porter e Quargo.
Il Gruppo ha sede a Pontedera (Pisa, Italia) e dal 2003 è
controllato da Immsi S.p.A., holding industriale facente capo a Roberto Colaninno, che ricopre la carica di Presidente
e Amministratore Delegato del Gruppo Piaggio.
Sul piano della produzione, il Gruppo Piaggio opera nel
mondo con una serie di stabilimenti situati a: Pontedera
(Pisa), Noale e Scorzè (Venezia), Mandello del Lario
(Lecco), Martorelles (Barcellona, Spagna); Baramati
(India, nello stato del Maharashtra), Vinh Phuc (Vietnam).
Il Gruppo Piaggio opera inoltre con una società in joint venture in Cina (a Foshan, nella provincia del Guangdong). Il
Gruppo Piaggio nel 2009 ha complessivamente venduto nel
mondo 607.700 veicoli di cui 410.300 nel business due ruote e 197.400 nel business dei veicoli commerciali.
Di grande rilievo, per la produzione motociclistica del
Gruppo Piaggio, sono le attività racing. Il Gruppo vanta infatti, nel proprio portafoglio di brand, marchi facenti parte
a pieno titolo della storia del motociclismo sportivo mondiale, con un palmarès complessivo di 95 campionati mondiali conquistati nelle varie specialità e oltre 500 vittorie
nelle varie specialità. Tra i marchi del Gruppo, Aprilia con
45 titoli mondiali e 278 vittorie nei G.P. è il marchio italiano e europeo più vincente nella storia del Motomondiale.
The engineer Paolo Nesti graduated in Mechanical
Engineering. Since 1988, the focus of his work has been on
engines. Presently he is responsible for the design of engines and for computational systems at the Centro Tecnico
Motori 2 Ruote of Pontedera. This Piaggio Group Center is
dedicated to the development of two-wheeler vehicle power
engines.
1. What is or should be the role of innovation in the
industrial and entrepreneurial world?
Nowdays the market has enlarged itself and Global
competition is our new work environment and we are not
L'ing Paolo Nesti è laureato in ing. Meccanica, in Piaggio
dal 1988, si è sempre occupato di motori. Oggi è il responsabile della Progettazione Motori e Sistemi di Calcolo
del Centro Tecnico Motori 2 Ruote di Pontedera, dove si
sviluppano tutti i motopropulsori per i veicoli a 2 ruote
del Gruppo.
1. Che spazio ha (e dovrebbe avere) l’innovazione nel
mondo industriale/impresariale?
La competizione globale a cui siamo chiamati non può es-
able to win our challenge playing on the simple grounds of
cost reduction. A large group like ours, which operates on
all major world markets, must be in a position of
competitive advantage based on providing products more
attractive to the customer, most original, high quality: we
can achieve this goal looking at the expressed and latent
Customers requirements even if they are also extremely
different from themselves because economic, lifestyle and
consumption reasons: in a word, we absolutely must
innovate. Only in this way we can create products that
ensure profitable business of the Company. Our group was
very clear this need.
Finally in order to achieve this goal, anything but simple,
we must put attention to the market, to extensive technical
expertise often interdisciplinary, to ability to express and
synthesize new solutions, to fast implementation of ideas
into products, to process control and to organization.
2. What are the strategies for innovation and quality
assessments pushing innovation?
In order to innovate the right prerequisites are the
following ones:
• to be very knowledgeable about both the product and
customer;
• to have the expertise on technology and product
knowledge of the best competitors;
• to be ensure that the work environment is "creative",
giving space to persons who may contribute to the
creation of ideas and having care to them encouraging
their development aims by providing preferential
channels for such projects.
The MP3 version and Hybrid are strictly examples of this
approach: the original idea was quickly passed to the
development objective by providing our customers the best
technology available on the market today (from a vehicle
structure enhanced by a revolutionary hybrid engine based
on a 4-stroke ie Euro3 with integrated management of the
two engines, ride-by-wire, lithium batteries, plug-in
without external power supply, electric reverse, etc.)…
sere giocata sul semplice terreno della riduzione dei costi.
Un grande Gruppo come il nostro, che opera su tutti principali mercati mondiali, deve porsi in una posizione di
vantaggio rispetto alla Concorrenza basandosi sull'offerta
di prodotti più attraenti per il Cliente, più originali, di
elevata qualità globale, intendendo con questo termine
anche e soprattutto la rispondenza ai bisogni espressi o
latenti di Clienti anche estremamente diversi tra di loro
per esigenze, contesti economici, stili di vita e di consumo: in una parola, deve fare innovazione. Solo in questo
modo potrà realizzare prodotti profittevoli che garantiscano l'attività dell'Azienda. Il nostro Gruppo ha ben chiara
questa necessità.
Per raggiungere questo obiettivo, tutt'altro che semplice,
occorrono attenzione al mercato, vaste competenze tecniche spesso interdisciplinari, capacità di esprimere e sintetizzare nuove soluzioni, velocità nell'implementazione
delle idee in prodotti, controllo dei processi ed organizzazione.
2. Quali sono le strategie per essere innovativi e quali
valutazioni spingono all’innovazione?
Per poter fare innovazione bisogna prima di tutto essere
profondi conoscitori sia del prodotto sia della clientela,
avendo le competenze specifiche sulle tecnologie e la conoscenza dei prodotti dei migliori concorrenti; occorre poi
far sì che l’ambiente di lavoro sia “creativo”, dando spazio alle persone che possono contribuire alla nascita delle idee e favorendone lo sviluppo predisponendo canali
preferenziali per tali progetti.
L’MP3 prima e la versione Hybrid dopo sono un esempio di
questo tipo di approccio: dall’idea originale si è passati in
breve tempo allo sviluppo finalizzato, mettendo a disposizione dei clienti la miglior tecnologia disponibile ad oggi sul mercato (un veicolo dalla struttura rivoluzionaria
impreziosito da un motore ibrido basato su un 4T i.e. Euro
3, dotato di gestione integrata dei due propulsori, rideby-wire, batterie al litio, plug-in senza alimentatore esterno, retromarcia elettrica, etc.).
3. Che ruolo ricoprono gli strumenti CAE e di prototipazione virtuale in tal senso?
L'innovazione in campo industriale parte da un'idea che, attraverso stadi successivi di maturazione, si trasforma in
uno o più prodotti che generano profitto per l'impresa. Questo processo non è
spontaneo; passa bensì per una serie di
verifiche ed eventuali correzioni, che
determinano il tempo necessario per
passare da idea a profitto. È quindi cruciale che queste attività siano veloci
senza perdere accuratezza; gli strumenti CAE contribuiscono ad accelerare il
processo, consentendo di ridurre i cicli
di sperimentazione fisica che richiedono notevole dispendio di tempo e quin-
3. What role do the CAE and virtual
prototyping tools in this regard?
Innovation in industry starts with an idea
that, through successive stages of
maturation, changes in one or more
products that generate profits for the
company. This process is not spontaneous,
but it is composed by multiple checks and
corrections, which determines the time it
takes to go from idea to profit.
Therefore it is crucial that these activities
are fast without losing accuracy and the
CAE tools help speed up the process,
reducing, for example, the cycles of
physical
experimentation
saving
considerable time and therefore money.
In the early stages of development of an innovative idea
the checks mentioned above are possible only at a
conceptual level, the details are not yet available for
physical prototypes At this level the simulation is the only
way to correct any abuses of the process of maturation.
4. How user needs have changed in recent years?
User requirements have been prompted by a significant
level of integration of CAE techniques and actually these
technologies are completely integrated in the process
design of product development.
It obviously implies that the complexity of the simulation
increase and, at the same time, the numerical results should
be produced in more little time; and it seems to be a
paradoxical situation.
CAE Users therefore need intensive tools interfaced with
those used in other business areas such as CAD software and
processing of experimental data, another requirement is the
ability to simulate not only the separate components, but
also systems to study the interactions between
components. This work field requires software tools fast,
robust and accurate, and hardware with the maximum
possible power from various points of view (processors,
RAM, CPU, etc.)… All these things are strictly necessary
without ever losing sight of the overall objective and
having clear theoretical principles that govern the software
used.
5. What are the advantages pointed out in his
professional experience and how has it changed its
approach to the design/production?
The advantages are actually well known to all actors
(engineers, managers): first of all the savings in time and
obviously money, having care to make virtual models (CAD,
Multibody, FEM) analysis and CFD studies for engine
performance, analysis of cooling, etc…
The primary purpose of this type of activity, but not the
only one, is to minimize the construction of physical
prototypes, thus avoiding the long series of validation
tests, limiting this activity to a stage "ripe" for the project.
The construction of prototypes takes place when the phase
23
di di denaro. Nelle fasi precoci di elaborazione dell'idea
innovativa le verifiche prima citate sono inoltre possibili
solo a livello concettuale, non essendo ancora disponibili
i dettagli per realizzare prototipi fisici: a questo livello la
simulazione rappresenta l'unico strumento per correggere
eventuali derive del processo di maturazione.
4. Come sono cambiate le esigenze degli utilizzatori negli ultimi anni?
Le esigenze degli utenti sono state indotte dal sensibile
livello d'integrazione che le tecniche CAE hanno ottenuto
nel processo di sviluppo dei prodotti. Questa circostanza
ha richiesto e continua a richiedere simulazioni sempre
più complesse e, sebbene questo possa sembrare paradossale, sempre più veloci. Gli utenti CAE hanno perciò bisogno di strumenti fortemente interfacciati con quelli usati
in altre aree aziendali, come i software CAD e di elaborazione dei dati sperimentali; un'altra esigenza è la possibilità di simulare non solo componenti isolati, ma anche sistemi, per studiare le interazioni fra componenti. Questo
quadro richiede strumenti software veloci, robusti e accurati, e hardware con la massima potenza possibile sotto
vari punti di vista (processori, memoria RAM, CPU, ecc.).
Il tutto senza mai perdere di vista l’obiettivo globale ed
avendo chiari i principi teorici che sovrintendono gli applicativi utilizzati.
5. Quali vantaggi ha rilevato nella sua esperienza professionale e come è cambiato il suo approccio alla progettazione/produzione?
I vantaggi sono oramai noti a tutti: prima di tutto il risparmio di tempo e quindi di denaro facendo modelli virtuali (CAD, Multidody, FEM), analisi e studi CFD per le prestazioni dei motori, analisi di raffreddamento, etc.
Lo scopo primario di questo tipo di attività, ma non il solo, è ridurre al minimo la costruzione di prototipi fisici
evitando così la lunga serie di prove di validazione, limitando questa attività ad una fase “matura” del progetto.
La costruzione dei prototipi avviene quando la fase di calcolo (e di ottimizzazione) è stata completata, riducendo
così la probabilità di dover apportare costose correzioni
calculation (and optimization) has been completed, thus
reducing the likelihood of having to make costly
adjustments to physical parts.
The second key issue concerns the quality of the project:
using CAE tools intelligently, we can quickly arrive at a
definition of optimal projects, thus laying the foundation
for a quality product.
The third aspect is rewarding management and sharing of
information: in this development process, it is essential to
share information in real time and records management, to
speed up internal processes of decision, correction,
approval, etc… and then once again reduce the risk of
introducing errors.
6. What was the contribution of EnginSoft and how it has
helped to enhance quality, capability and capacity of its
industry/company?
EnginSoft was invaluable in training, both basic and
learning new software, even with the help of TCN. Basic
education is key to preventing senseless and unconscious
use of CAE tools: a real risk because of the simplicity and
widespread use of software that claims to be based on
complex theoretical apparatus.
EnginSoft has also played and still plays a vital role in the
innovation process, enabling access to technical and
software embedded in a significant way with other
development activities, and promoting effective networking
among users, for example conferences and meetings with
the resonance increasing year after year.
7. What prospects he sees for the calculation codes in
relation to the challenges of the future?
It 'is now widely believed that competitive, if not survival,
of different firms in the Old Continent and in the western
world, in general, must be based on knowledge and
innovation content of the products: the old standards of
competitiveness are indeed falling down because the real
big power of the new countries and these new ‘world’ will
become strong players in the world economy. The
instruments that promote the enrichment of science and
technology products are becoming so indispensable to be
su pezzi fisici. Il secondo aspetto fondamentale riguarda
la qualità del progetto: utilizzando con intelligenza gli
strumenti CAE, si può arrivare rapidamente ad una definizione ottimale dei progetti, ponendo così le basi per un
prodotto di qualità.
Il terzo aspetto premiante è la gestione e la condivisione
delle informazioni: in questo processo di sviluppo è fondamentale la condivisione delle informazioni in tempo
reale e la gestione della documentazione per velocizzare i
processi interni di decisione, correzione, approvazione,
etc. e quindi ridurre ancora una volta i rischi di introdurre errori.
6. Qual è stato il contributo di EnginSoft e in che modo
ha saputo valorizzare qualità, potenzialità e capacità
della sua industria/impresa?
EnginSoft è stata preziosa nel campo della formazione, sia
a livello base che di apprendimento di nuovi software, anche con il contributo di TCN. La formazione di base è fondamentale per evitare usi scriteriati e inconsapevoli degli
strumenti CAE: rischio concreto e diffuso a causa della
semplicità d'uso di software che pure si basano su apparati teorici complessi.
Enginsoft ha inoltre ricoperto e tuttora ricopre un ruolo
basilare nell'ambito dell'innovazione di processo, rendendo possibile l'accesso a tecniche e software integrabili in
modo significativo con le altre attività di sviluppo, e promuovendo con efficacia il networking fra utenti, per
esempio con conferenze e incontri di risonanza crescente
anno dopo anno.
7. Che prospettive intravede per i codici di calcolo in relazione alle sfide poste dal futuro?
È ormai convinzione diffusa che la competitività, se non
la sopravvivenza, delle imprese del Vecchio Continente e
del mondo occidentale in genere dovrà poggiare sulla conoscenza e sul contenuto innovativo dei prodotti; i vecchi canoni di competitività si stanno infatti sfaldando di
fronte ai paesi che sono divenuti protagonisti dell'economia mondiale. Gli strumenti che favoriscono l'arricchimento scientifico e tecnologico dei prodotti stanno divenendo perciò indispensabili per riuscire a rimanere nel mercato; i codici di calcolo
appartengono a tale categoria ed è perciò prevedibile che la loro evoluzione da
prodotti di nicchia a strumenti di uso
corrente si completi nei prossimi anni,
accompagnata dall'accelerazione della
loro potenza ed efficienza, resa possibile
dall'analoga tendenza in campo hardware.
8. Quali progetti, obiettivi e nuovi traguardi intende perseguire grazie all’uso
di questi strumenti?
Ritengo che nel medio termine non si verificheranno cambiamenti sostanziali nel-
25
able to stay in the market, the
computer codes belong to this category
and it is therefore like absolutely sure
that their evolution from niche
products to use current tools will be
completed in the nextg years, and it
will be accompanied by the
acceleration of their power and
efficiency, and it will be made possible
from the analogous trend in the field
hardware.
8. What plans, objectives and new
goals will be pursued through the use
of these tools?
I believe that in the medium term there
will be no substantial changes in the use of CAE tools in
Piaggio; during trouble-shooting in phase its usage has
become a minority compared to the prediction, and it is
evident that the products are developed today with growing
contribution of the simulations.
To predict the spread of multi-disciplinary optimization
techniques will be Piaggio road map in this area, and the
integration between CAE tools available today from various
related subjects could push this design-way just as it
happens between fluid dynamics and mechanics cold
thematic.
The number of experimental procedures for the qualification
and a relative fee CAE activity will increase in the next
future, so that physical tests will be conducted on
prototypes already developed and optimized in terms of
simulation, thereby increasing the likelihood of success of
the test.
In general, the use of CAE techniques will "dominate" more
and more products in the sense that you can know more
deeply the physical behavior, with clear benefits in terms of
quality and reliability.
9. And what we hope for the world of scientific
technology to the continuing search for a dimension of
creativity and competitiveness?
The synthesis between creativity and competitiveness gets
through the tools that technology provides. The task of
scientific technology is just to make simple evaluations and
complex activities that hinder the creativity of the people,
thus removing the obstacles that typically prevent you from
looking up to new ideas. It will be increasingly necessary to
have integrated multidisciplinary tools, in order to further
improve the aspects that are now viewed individually.
Optimizers, being able to interact with different
disciplinary tools, they have a high development potential
that any company can develop applications specifically for
doing their business. Also in this area Piaggio has already
made some experiences and others are being set
(modeFRONTIER and application specific simulation engine)
to maximize engine performance and reduce development
time for new products.
l’uso degli strumenti CAE in Piaggio: l'uso in fase troubleshooting è divenuto minoritario rispetto a quello predittivo, indicando che i prodotti vengono sviluppati oggi con
contributo crescente da parte delle simulazioni.
Prevedo per Piaggio una diffusione delle tecniche di ottimizzazione multi-disciplinare, favorita dall'integrazione
spinta oggi disponibile fra strumenti CAE afferenti da diverse materie, come ad esempio la fluidodinamica e la
meccanica fredda.
Aumenterà il numero di procedure di qualifica sperimentale con un corrispettivo CAE, in modo che i test fisici siano condotti su prototipi già studiati e ottimizzati a livello di simulazione, aumentando così la probabilità di successo della prova.
In generale, l'uso delle tecniche CAE consentirà di "dominare" sempre più i prodotti, nel senso che sarà possibile
conoscerne sempre più a fondo il comportamento fisico,
con evidenti benefici in termini di qualità ed affidabilità.
9. E cosa si auspica per il mondo della tecnologia scientifica alla continua ricerca di una dimensione tra creatività e competitività?
La sintesi tra creatività e competitività passa proprio attraverso gli strumenti che la tecnologia mette a disposizione. Compito della tecnologia scientifica è appunto
quello di rendere semplici le valutazioni e le attività complesse che ostacolano la creatività delle persone, rimuovendo così gli ostacoli che tipicamente impediscono di alzare lo sguardo verso nuove idee. Sarà sempre più necessario avere strumenti multidisciplinari integrati, per poter
migliorare ancora gli aspetti che ora sono visti singolarmente.
Gli ottimizzatori, potendo interagire con diversi strumenti multidisciplinari, hanno un elevato potenziale di sviluppo che ogni azienda può sviluppare facendo applicazioni
ad hoc per le proprie attività. Anche in questo settore
Piaggio ha fatto già alcune esperienze e altre sono in corso di impostazione (modeFRONTIER e applicativi specifici
di simulazione motore) per massimizzare le prestazioni dei
motori e per ridurre il tempo di sviluppo dei nuovi prodotti.
modeFRONTIER Used in the Design of
Fatigue-Resistant Notches
evolved variable-radius notches in trees, bones, etc; the
German engineer Claus Mattheck showed that similar
concepts could be applied to engineering structures.
Professor David Taylor at Trinity College Dublin in Ireland
wondered whether the variable-radius notch could be
treated as an optimisation problem, and decided to use
mF to solve it. Working with Matteo Toso and Professor
Luca Susmel of the University of Ferrara in Italy, they
considered the problem of a 90° fillet and used mF to seek
for solutions within a design space consisting of different
variable-radius fillets. They were able to find solutions
better than those previously obtained using other
methods, achieving reductions in the maximum stress of
more than a factor of two.
Fig. 1 - Researchers at Trinity College Dublin used modeFRONTIER
in the Design of Fatigue-Resistant Notches
Researchers at Trinity College Dublin in Ireland have used
modeFRONTIER (mF) software to reduce stress
concentration effects of notches and thus significantly
improve the fatigue resistance of components. Many
engineering components contain features such as notches
and fillets, which are usually designed with a constant
radius of curvature.
However it has long been known that this is not the best
solution.
Variable-radius notches, in which the radius of curvature
changes with position along the notch, can achieve much
lower stress concentration factors with negligible change
in the weight or size of the component. Nature has
Experimental work conducted on steel samples showed
that these predicted reductions translated exactly into
real improvements in the fatigue strength of the
components. Reductions in stress concentration factors
can be highly beneficial, allowing designers to save
weight, with consequent reductions in energy and material
costs, without sacrificing reliability. The approach
developed at Trinity College could be automated for use in
industrial design, using mF in conjunction with FEM, to
achieve real improvements in components of the future.
Prof. David Taylor M.R.I.A.,
Mechanical Engineering, Trinity College Dublin
For more information, please contact:
Professor David Taylor, [email protected]
Department of Mechanical and
Manufacturing Engineering
The Department of Mechanical and Manufacturing
Engineering undertakes research in a number of
selected themes, including; Bioengineering, Fracture
and Fatigue of Materials, Fluids, Acoustics and
Vibration, Fluids and Heat Transfer, Manufacturing
Technology and Systems, and Tribology and Surface
Engineering.
Fig. 2 - Finite element analysis of a variable-radius fillet in a bracket
component.
http://www.tcd.ie/mecheng/research/
27
A Multi-Objective Optimization with
Open Source Software
Sometimes it happens that a small-to-medium sized firm
does not benefit from the advantages that could be
achieved through the use of virtual simulation and
optimization techniques. This represents in many cases a
great limitation in the innovation of products and
processes, and this can lead, in a very short time, to a
complete exclusion from the market and to an inevitable
end.
Nowadays, it is mandatory to reduce as much as possible
the time-to-market, while always improving the quality of
products and satisfying the customer needs better that
the competitors. In some fields it is a question of “life or
death”.
According to our opinion, the main reasons that limit or,
in the worst case, make impossible the use of the virtual
simulation and optimization techniques can be grouped
into three categories:
1. These techniques are not yet sufficiently known and
the possible users do not have a great confidence in
the results. Sometimes physical experimentation,
guided by experience maturated through many years of
practice, is thought to be the only possible way to
proceed. This is actually wrong in the great majority of
cases, especially when new problems have to be
solved. A change of vision is the most difficult but
essential step to take in this context.
Rough Phase
Fine Phase
License
Many possibilities are
available
GNU license largely used or similar
versions with some restrictions
Development
Continuous improvement
and a clear guideline
Left to the community
Available features
State of the art
It strongly depends on “who” leads
the development. Sometimes, very
advanced
features can be available.
Technical support
Usually the distributor
offers a technical support
Usually no support is available but
in some cases forums can help
Usability
Easy-to-use and smart
GUIs
Some effort could be required to
the user
Customization
Only in some cases
If the source code is available the
possibility of customization and
development is complete
Table 1: The table compares some key features that characterize commercial
and open source software, according to our opinion.
2. Adequate hardware facilities considered necessary to
perform an optimization are not available and
therefore the design time becomes too long. We are
convinced that, in many cases, common personal
computers are enough to efficiently solve a large
variety of engineering problems. So, this second point,
which is often seen as an enormous obstacle, has to be
considerably downsized.
3. The simulation software licenses are much too
expensive given the firm’s financial resources. Even
though the large majority of commercial software
houses offer a low-cost first entry license, it is not
always immediately evident that these technologies
are not just an expense, but rather a good investment.
As briefly stated above, the second point often does not
represent a real problem; the most important obstacle is
summarized in the first point. People actually find it hard
to leave a well-established procedure, even if obsolete, for
a new one which requires a change in the everyday way of
working. The problem listed in the third point can be
solved, when possible, by using open source (see [1]),
free and also home-made software. It is possible to find,
with an accurate search on internet, many simulation
software systems which are freely distributed by the
authors (under GNU license in many cases). Some of them
also exhibit significant features that usually are thought
to be exclusive to commercial software.
As usual, when adopting a new technology, it is
recommended to consider both the advantages and the
disadvantages. We have compared in Table 1 some aspects
that characterize the commercial and the open source
codes which should be considered before adopting a new
technology.
Open source codes are usually developed and maintained
by researchers; contributions are also provided by
advanced users all over the world or by people who are
supported by research projects or public institutions, such
as universities or research centers. Unfortunately, this can
lead to a discontinuous improvement, not driven by a
clear guideline, but rather left to the free contributions
given by the community. On the contrary, commercial
software houses drive the development according to wellknown roadmaps which generally reflect specific industry
trends and needs.
Commercial software is usually “plug-and-play”: the user
has just to install the package and start using it. On the
contrary - but not always - open source software could
only open source software, are presented in
require some skill and effort in
this paper. We decided to use Scilab (see
compiling the code or adapting a
[2]) as the main platform to drive the
package to a specific system
configuration.
optimization process through its genetic
Software houses usually offer to the
algorithm toolbox. For the solution of the
structural problem, presented in the
customer technical support, which
following, we adopted two packages. The
can be, in some cases, really helpful
first one is the Gmsh (see [3]) to manage a
to make the investment profitable. An
internet forum, when it exists, is the
parametric geometry and mesh it; the
only way to have support for a user of
second one is CalculiX (see [4]), an FEM
solver. It is important to remember that
an open source code.
this choice is absolutely not mandatory, but
Another important issue is the
usability of the simulation software,
is strictly a matter of taste.
which is mainly given by a userfriendly graphical interface (often
The structural optimization problem
In this work a C-type press is considered, as
referred to as GUI). The commercial
software usually has sophisticated
the one shown in Figure 2. This kind of
geometry is preferred to other ones when
graphical tools that allow the user to Fig. 1 - An example of C-type press. The
easily manage and explore large steel C-shaped profile which will be optimized the force that has to be expressed by the
in this work is highlighted with a red line.
hydraulic cylinder is not very high, usually
models in an easy and smart way; the
not greater than roughly 200 [Ton]. The main advantages
open source codes rarely offer a similar suite of tools, but
of this type of press are essentially the relative low weight
they have simpler and less easy-to-use graphical
and volume of the machine and the possibility of
interfaces.
accessing the workbench
The different magnitude of the investment can explain all
from three sides.
these differences between the commercial and open
The dimensioning of the
source codes.
lateral C-shaped profiles
is probably one of the
However, there are some issues that can make the use of
most challenging phases
a free software absolutely profitable, even in an industrial
in the design process;
context. Firstly, no license is needed to run simulations:
the large majority of the
in other words, no money is needed to access the virtual
weight and cost, for the
simulation world. Secondly, the use of open source
mechanical part at least,
software allows to break all the undesired links with third
is actually concentrated
party software houses and their destiny. Third, the number
there. Consequently, a
of simultaneous runs that can be launched is not limited,
good designer looks for
and this could be extremely important when performing
the lightest profile which
an optimization process. Last, but not least, if the source
code is available all sorts of customizations are in
is able to satisfy all the
Fig. 2 - The C-shaped plate geometry has
structural requirments. been modeled using the dimensioning
principle possible.
Moreover, an economical drawn in this picture, together with the
The results of a structural optimization, performed using
configuration is also thickness TH of the plate.
Plate thickness [mm]
Plate max dimensions [m]
Available steel codes
desired, in order to reduce as much as possible the
production cost.
Vertical <4
20
A, B, C
Horizontal <2
When optimizing, the designer should also take into
30
account some aspects which are not strictly related to
Vertical <3
40
structural issues but are however important or, in some
A, B
Horizontal <2
50
cases fundamental, to deal with an optimal design. These
aspects could be related to the availability of materials
Table 2: The table collects some limitations in the steel plate provision.
and components on the market, technical norms that have
to be satisfied, marketing indications and more. In our
Young modulus Maximum stress /
Steel code
Cost [$/Kg]
case the steel plate supplier, for example, can provide only
[MPa]
Yield limit [MPa]
the configurations collected in Table 2.
A
200 (220)
1.2
It is clear that an optimization process that does not take
210000
B
300 (330)
2.3
into consideration these requisites could lead to
configurations which are optimal only from a theoretical
C
600 (630)
4.0
point of view, but which cannot be practically
Table 3: The maximum desired stress, the yield limit and the cost per unit
implemented. For example, a very light configuration is
weight for the three available steels.
Fig. 3 - A possible version of the C-shaped plate meshed in Gmsh.
Fig. 4 - The CalculiX GraphiX window, where the von Mises stress for the Cshaped plate is plotted.
not of practical interest, if it requires a steel characterized
by a yield limit greater that 600 [MPa].
For this reason all the requirements collected in Tables 2
and 3 have been included in order to drive the
optimization algorithm to feasible and interesting
solutions.
Moreover, it is required that the hollow in the plate (H2max(R1,R2) x V2, see Figure 2) is at least 500 x 500 [mm]
to allow the positioning of the transversal plates and the
hydraulic cylinder.
Another technical requisite is that the maximum vertical
displacement is less than 5 [mm] to avoid excessive
misalignments between the cylinder axis and the structure
under the usual operating conditions. This limit has been
chosen arbitrarily, in the attempt to exclude the designs
that are not sufficiently stiff, taking into account,
however, that the C-plate is a part of a more complex real
structure which will be much more stiff than what is
calculated with this simple model.
A designer should recognize that the solution of such a
problem is not exactly trivial. Firstly, it is not easy to find
a configuration which is able to satisfy all the requisites
listed above; secondly, it is rather challenging to obtain a
design that minimizes both the volume of the plate (the
weight) and the production cost.
29
The open source software for the
structural analysis
Gmsh has been used as a preprocessor to manage
the parametric geometry of the C-shaped plate and
mesh it in batch mode. Gmsh has the ability to mesh
a non-regular geometry using triangular elements;
many controls are available to efficiently define the
typical element dimension, the refinement depth
and more. It is a very powerful software tool which
is also able to manage complicated threedimensional geometries and efficiently mesh them
using a rich element library.
The mesh can be exported in a formatted text file
where the nodes and the element connectivities are
listed together with some useful information related
to the so-called physical entities, previously defined
by the user; this information can be used to correctly
apply, for example, boundary conditions, domain
properties and loads to a future finite element model.
The CalculiX finite element software has been used to
solve the linear elastic problem. Also in this case a batch
run is available; among the many interesting features that
this software offers are the easy input text format, and the
ability to perform both linear and non-linear static and
dynamic analyses.
CalculiX also offers a pre and post processing
environment, called CalculiX GraphiX, which can be used
to prepare quite complicated models and, above all,
display results.
These two software tools are both well documented and
also some useful examples are provided for new users. The
input and output formats are, in both cases, easy to
understand and manage.
In order to make the use of these tools completely
automatic, it is necessary to write a procedure that
translates the mesh output file produced by Gmsh into an
input file readable by CalculiX. This translation is a
relatively simple operation and it can be performed
without a great effort using a variety of programming
languages; a text file has to be read, some information
has to be captured and then rewritten into a text file
using some simple rules. For this, a simple executable file
(named translate.exe) has been compiled and it will be
launched whenever necessary.
A similar operation has also to be performed in an
optimization context to extract the interesting quantities
from the CalculiX result file and rewrite them into a
compact and accessible text file.
As before, an executable file (named read.exe) has been
produced to read the .dat results file and write the
volume, the maximum vertical displacement and the nodal
von Mises stress corresponding to a given design into a
file named results.out.
Many other open source software codes are available, both
for the model setup and for its solution. Also for the
results visualization, there are many free tools with
powerful features. For this reason the interested reader
can imagine the use of other
tools to solve this problem in an
efficient way.
These routines are extremely flexible
and they can be modified by the user
according to his or her own needs,
H1
250
150.
5
since the source code is available. This
H2
500
1500
5
The optimization process driven
is exactly what we have done,
V1
250
1500
5
by Scilab
modifying the optim_moga.sci script to
V2
500
1500
5
The genetic algorithm toolbox, by
handle the constraints (with a penalty
V3
250
1500
5
Yan Collette, is available in the
approach) and manage the infeasible
R1
50
225
5
standard installation of Scilab
designs efficiently (i.e.: all the
R2
50
225
5
and it can be used to solve the
configurations which cannot be
multi-objective
optimization
computed); we have then redefined the
TH
20
50
10
problem described above. This Table 4: The lower and upper bounds together with the
coding_ga_binary.sci to allow the
step
for
the
input
variables.
toolbox is composed of some
discretization of the input variables as
listed in Table 4. Other
max vM
max vertical
Volume
Design
H1
H2
V1
V2
V3
R1
R2
TH
Cost
stress
displacement
small changes have been
name
[mm]
[mm]
[mm]
[mm]
[mm]
[mm]
[mm]
[mm]
[$]
[mm ]
[MPa]
[mm]
made to the routines to
A
670
665
575
500
490
165
110
20
1304
577.7
4.93
3.53•10
perform some marginal
operations, such as writing
B
1155
695
725
545
840
185
165
30
1097
199.8
1.73
1.06•10
partial results to a file.
Table 5: The optimal solutions.
When the genetic algorithm
requires the evaluation of a
routines which implement both a MOGA and a NSGA2
given configuration, we run a Scilab script which is
algorithm and also a version for the operations that have
charged to prepare all the text files needed to perform the
been performed when running a genetic algorithm, that is
run and then launch the software (Gmsh, CalculiX and the
the encoding, the crossover, the mutation and the
other executables) through a call to the system in the
selection.
right order. The script finally loads the results needed by
the optimization.
Variable
Lower bound
[mm]
Upper bound
[mm]
Step
[mm]
3
7
8
Fig. 5 - The Cost of the computed configurations can be plotted versus the Volume. Red points stand for the feasible configurations while the blue plus indicates the configurations that do not respect one constraint at least.
The two green squares are the Pareto (optimal) solutions (A and B in Table 5).
Fig. 6 - The vertical displacement for the design A.
Fig.7 - The von Mises stress for the design A.
It is important to highlight
that this script can be easily
changed to launch other
software tools or perform other
operations whenever necessary.
In our case, eight input
variables are sufficient to
completely parameterize the
geometry of the plate (see
Figure 2): the lower and upper
bounds together with the steps
are collected in Table 4. Note
that the lower bound of
variable V2 has been set to 500
[mm], in order to satisfy the
constraint on the minimal
vertical dimension required for
the hollow.
We can use a rich initial
population, (200 designs
randomly
generated),
considering the fact that a high
number of them will violate the
imposed constraints, or worse,
be unfeasible. The following
generations
will
however
consist of only 50 designs, to
limit the optimization time.
31
After 50 generations we obtain
the results plotted in Figure 5
and Table 5, where the two
Pareto (optimal) solutions are
collected. We finally decided to
choose, between the two
optimal ones, the configuration
with the lowest volume (named
as “A” in Table 5).
In Figures 6 and 7 the vertical
displacement and the von Mises
Fig. 9 - The von Mises stress for the modified design.
stress are plotted for the Fig. 8 - The vertical displacement for the modified
design.
optimal configuration named
“A” (see Table 5). Note that
during the optimization, the maximum value of the von
input variables, since the output does not strongly
Mises stress computed in the finite element Gauss points
dependent on them, and this leads to a simpler
has been used, while in Figure 7 the von Mises stress
optimization problem.
extrapolated by CalculiX to the mesh nodes is plotted; this
The cost does not change; actually it represents the cost
is the reason why the maximum values are different.
of the rectangular plate needed to produce the C-shaped
However, they are both less than the yield limit
profile.
corresponding to the steel type C, as reported in Table 3.
Other configurations with a lower volume can be probably
Horizontal and vertical
max vM max Vertical Volume
found with some other runs; however, the reader has to
Cost
displacement
length of cuts starting
stress
[$]
[mm
]
consider that these improvements are not really
[mm]
from corners [mm]
[MPa]
significant in an industrial context, where, probably, it is
H1/3
1304
581.3
4.80
3.33•10
much more important to find optimal solutions in a very
short time.
Table 6: The modified design. It can be seen that there is an interesting
3
7
reduction in the volume with respect to the original design, the “A” configuration in Table 5. Other output quantities do not present significant variations.
Another interesting consideration is that the Pareto front
in our case consists of just two designs: this shows that
the solution of this optimization problem is far from
trivial.
The design of the C-shaped plate can be further improved.
If we run other generations with the optimization
algorithm better solutions could probably be found, but
we feel that the improvements that might be obtained in
this way do not justify additional computations.
Substantial improvements can be achieved in another way.
Actually, if we look at the von Mises stress distribution
drawn in Figure 7 we note that the corners of the plate do
not have a very high stress level and that they should not
influence the structural behavior very much.
A new design can be tested, cutting the corners of the
plate; for the sake of simplicity we decided to use four
equal cuts of horizontal and vertical dimensions equal to
H1/3, starting from the corners. The results are drawn in
Figures 8 and 9, which can be compared with Figures 6
and 7.
As expected, there is a reduction in volume with respect
to the original design, but no significant variations are
registered in the other outputs. This corroborates the idea
that the cut dimensions can be excluded from the set of
Conclusions
In this work it has been shown how it is possible to use
open source software to solve a non-trivial structural
optimization problem.
Some aspects which characterize the commercial and the
open source software have been stressed in order to help
the reader to make his or her own best choice. We are
convinced that there is not a single right solution but
rather that the best solution has to be found for each
situation.
Whichever the choice, the hope is that virtual simulation
and optimization techniques are used to innovate.
References
[1] Visit http://www.opensource.org/ to have
information on open source software
[2] Scilab
can
be
freely
downloaded
http://www.scilab.org/
[3] Gmsh
can
be
freely
downloaded
http://www.geuz.org/gmsh/
[4] Calculix can be freely downloaded
http://www.calculix.de/
more
from:
from:
from:
Contacts
For more information on this document please contact the
author:
Massimiliano Margonari - Enginsoft S.p.A.
[email protected]
ANSYS 13: Il punto sui solutori per
modelli di grandi dimensioni nelle
simulazioni meccaniche
Una delle grandi sfide per i software di simulazione basati sul
metodo degli elementi finiti è l’efficienza nel trattare modelli di grandi dimensioni, e quindi:
• di conservare i dettagli presenti nei modelli CAD;
• di avere risultati accurati;
• di disporre di algoritmi veloci e robusti per la meshatura;
• di disporre di CPU sia su desktop che su cluster.
In particolare è sempre più vero che il costo della CPU è inferiore al costo uomo, e cioè che, in presenza di algoritmi affidabili per la meshatura di modelli di grandi dimensioni,
conviene ricorrere a questi piuttosto che svolgere un pesante lavoro di “defeaturing” e di meshatura semiautomatica.
via numerica nel campo delle applicazioni meccaniche. Nel
passato infatti l’elaborazione numerica è sempre stata assegnata alle potenzialità della CPU in una architettura in cui la
CPU svolgeva un ruolo centralizzato. Oggi, invece, i principali produttori di schede grafiche hanno messo a punto nuove
architetture che permettono incrementi consistenti delle prestazioni grafiche: la novità sta nella capacità di sfruttare il
gran numero di ALU (Arithmetic Logic Unit) per eseguire algoritmi in parallelo. Seguendo la comparsa nel tempo di queste soluzioni si può far riferimento alle schede progettate da
nVIDIA con tecnologia CUDA e dalla ATI con tecnologia
STREAM.
ANSYS a sua volta ha sviluppato algoritmi paralleli che eseguono calcoli in doppia precisione sfruttando le risorse relative alla tecnologia “GPU based”.
In generale e per comprendere l’attenzione dedicata da
ANSYS al problema di accelerare l’analisi si può far riferimento anche alle tecnologie disponibili nelle precedenti versioni. Queste tecnologie, del resto, sono state rese ancora più
efficaci nell’ambito degli aggiornamenti sviluppati da ANSYS.
Si richiamano:
SMP (Shared memory Processing), tecnologia consistente in
un’architettura di più CPU che condividono la stessa memoria.
DMP (Distributed Memory), tecnologia consistente in un’architettura di più CPU con una porzione di memoria dedicata
a ciascuna CPU.
All’aspetto dei costi si affianca - ed è più importante di questo - l’aspetto dell’affidabilità dei risultati. Esso dipende in
larga parte dalla qualità del modello e quindi anche della
mesh.
La release 13 del codice ANSYS Mechanical offre una risposta
molto convincente a questi problemi, trattati in ottica industriale. Infatti:
• orienta all’High Performance Computing consentendo
l’uso di CPU diverse;
• produce modelli schematizzati automaticamente in
maniera adeguata;
• contiene acceleratori specifici.
La novità della release R13 di ANSYS, infatti sta nel saper
adattare il nuovo paradigma di processamento del calcolo per
Se si confrontano queste due architetture solamente sulla base del tempo di calcolo risulta più efficiente la tecnologia
DMP, sua volta più costosa dal punto di vista dell’hardware.
Il vantaggio della tecnologia DMP rispetto al SMP risulta però inferiore se il tempo di calcolo è misurato come intero
“elapsed time”, intendendo con questo il tempo relativo all’intero processo incluse le fasi precedenti e successive all’analisi vera e propria.
Se quindi si ragiona in base al “dpd” (design produced per
day) il rapporto di efficienza DMP/SMP è meno significativo.
Più precisamente questo confronto è valido fino ad 8 CPU
perché al di sopra di questo numero la SMP satura ed la DMP
diventa oltremodo vantaggiosa anche in termini di “dpd”.
Altra tecnologia del software ANSYS per ridurre i tempi di
esecuzioni delle analisi è la VT (Variational Technology) che
implementa gli algoritmi di Taylor, Pade’ e Roms.
Essa non può però essere utilizzata in tutti i casi. Si applica
ad analisi termiche, ad analisi in frequenza e anche ad alcuni problemi di non linearità strutturali quali le tematiche di
creep. Non possono, però, essere presenti nel modello elementi CONTACT e questo, per certi versi, è il limite di tale approccio.
Infine è utile ricordare quanto certe metodologie di analisi di
ben solida ed antica applicazione siano utili e rinnovabili
nelle situazioni più complesse e quanto queste stesse tecniche possano beneficiare comunque delle generali accelerazioni legate all’aumento delle capacità di calcolo (esempio “GPU
technique”).
Ricordandole brevemente esse sono:
• Submodelling: valutazione locale del gradiente delle tensioni in situazioni alla De Saint Venant
• Substructuring: riduzione del modello a condensazioni di
masse e rigidezze e ripetizione delle stesse per parti del
modello ripetitive
• CMS: Component Mode Synthesis è una specie di sottostrutturazione con accoppiamento delle zone di interfaccia tramite equazioni di ‘coupling’
I tre sistemi sono stati rivisti nell’ottica dei miglioramenti
progettati per la nuova release.
Per concludere uno sguardo al futuro: le tecnologie per l’accelerazione della velocità di calcolo richiedono parallelamente il potenziamento dell’hardware. Gli sviluppi previsti in
ANSYS tengono in conto l’evoluzione nell’hardware per migliorare le prestazioni. La release 13 rappresenta quindi un
primo passo nell’adattamento delle metriche della tecnologia
GPU, finalizzato a migliorare la scalabilità del software in
tutte le applicazioni seguendo così quanto già fatto con successo ad esempio nelle applicazioni relative alla CFD.
Per maggiori informazioni:
Emiliano D’Alessandro - EnginSoft
[email protected]
La simulazione di sistema in ANSYS:
Simplorer
La release 13 di ANSYS lega nello stesso ambiente le tecnologie per la simulazione elettromagnetica in bassa ed
alta frequenza prodotte da Ansoft. Di queste, abbiamo dato informazione in edizioni precedenti della newsletter.
Ci occupiamo qui invece di Simplorer, la tecnologia per la
simulazione di sistema in ANSYS.
Simplorer è un software di simulazione Multi-Domain che
consente di modellare, simulare, analizzare e ottimizzare
sistemi complessi, come sistemi elettromagnetici, elettromeccanici, elettrotermici, e più in generale, meccatronici
e cibernetici.
Se quindi da un lato ANSYS fornisce strumenti per la modellazione e la simulazione di singoli componenti in diverse fisiche e discipline, dall’altro, attraverso una tecnologia
come Simplorer, essa consente la simulazione a livello di
sistema. In altre parole vengono messe a disposizione metodologie e tecniche affinché singoli componenti possano
essere analizzati simultaneamente in un unico modello,
tenendo in considerazione le mutue interazioni tra di essi.
L’utilizzo delle caratteristiche di modellazione di Simplorer
consente quindi ai progettisti di realizzare prototipi virtuali considerando tutti gli aspetti ed i componenti di un
sistema, quali ad esempio i componenti elettronici, i sensori, gli attuatori, i motori elettrici ed i generatori, i propulsori ibridi, i convertitori di potenza così come i con-
33
Fig. 1 - Simplorer in interfaccia ANSYS WB.
Fig. 2 - Modelli e linguaggi per la simulazione di sistema in Simplorer.
Fig. 3 - Link dinamico tra HFSS-Simplorer (a) e SIwave-Simplorer (b).
trolli ed i software embedded.
Una tale metodologia si realizza attraverso l’implementazione di schemi circuitali, modelli analitici ed a parametri
concentrati, circuiti equivalenti, tecniche di cosimulazione, reti multi-livello ecc…
Di seguito vengono analizzate alcune delle principali caratteristiche di Simplorer:
1) Tecniche di modellazione
Simplorer offre diverse tecniche di modellazione inclusi
circuiti, diagrammi a blocchi, macchine a stati, equazioni
e linguaggi di modellazione come il linguaggio VHDL-AMS,
il SML (Simplorer Modeling Language) ed il C/C++.
L’impiego simultaneo di tali strumenti consente di modellare sistemi caratterizzati da segnali analogici, digitali o
analogico-digitale. Questo approccio elimina la necessità
di effettuare trasformazioni matematiche, tipicamente
soggette ad errori.
Una tale flessibilità nelle tecniche di modellazione fa di
Simplorer uno strumento molto efficace all’interno di un
gruppo di lavoro poiché professionisti di diversa estrazione tecnica possono far confluire modelli realizzati con linguaggi diversi all’interno dell’unica piattaforma di simulazione di Simplorer.
In Figura 2 una sintesi delle tecniche
di modellazione a disposizione di
Simplorer.
ti realizzati in SIwave e HFSS. Tale procedura si basa sulla valutazione e caratterizzazione a parametri S di un modello FEM.
Tipicamente, una volta definite opportunamente le porte
di input ed output nei modelli agli elementi finiti, SIwave
e HFSS consentono infatti di esportare la matrice di scattering verso Simplorer.
Come mostrato in Figura 3 il link SIwave-Simplorer consente di effettuare in Simplorer analisi di Signal integrity
su schede PCB, mentre l’integrazione di HFSS permette
l’analisi elettromagnetica di sistema anche in alta frequenza.
Le tecniche con le quali è possibile includere modelli realizzati con altri software di casa ANSYS sono in particolare due: La tecnica della cosimulazione e la tecnica della
model order reduction (MOR).
La cosimulazione o “Co-Simulation” (co-operative simulation) è una metodologia di simulazione che consente a
componenti singoli di essere simulati in maniera simultanea da differenti software. Questa tecnologia permette
quindi ai due software di scambiarsi informazioni, quali ad
esempio boundary conditions o time steps, in maniera collaborativa e sincronizzata.
2) Physics-based modeling
Per modelli per i quali è richiesto un
elevato livello di accuratezza,
Simplorer fornisce un link diretto ad
altri software ANSYS, tra questi:
Maxwell, Q3D Extractor, RMxprt,
PExprt, HFSS, SIwave, ANSYS Icepak,
ANSYS Rigid Dynamics e ANSYS
Mechanical.
In particolare dall’ultima versione
(Simplorer 9.0.1) è possibile integrare
all’interno della simulazione di
Simplorer i modelli agli elementi fini-
Fig. 4 - Control Design per il modello multy-body di un braccio di un escavatore in ANSYS WB.
35
analisi parametriche, di ottimizzazione, di sensitività, e di tuning al fine di ottenere un progetto ottimizzato, in relazione a criteri di performance fissati, raggiungendo il miglior trade-off
possibile.
In questo senso Simplorer può usufruire di tutta
la potenza di calcolo a disposizione perché in
grado di effettuare analisi distribuite.
In particolare, dall’ultima release, Optimetrics
viene incluso all’acquisto nel pacchetto software.
Fig. 5 - Analisi di sistema e circuit coupling in ANSYS.
Questo tipo di tecnica è implementabile con i modelli di
Maxwell e con i modelli Multy Body di ANSYS, per i quali
Simplorer fornisce gli eventuali controlli (Fig 4).
La tecnica della Model Order Reduction (MOR) è una disciplina della teoria dei sistemi e dei controlli che studia le
proprietà dei sistemi dinamici in modo tale da ridurne la
complessità, preservandone il comportamento agli ingressi
e alle uscite (input ed output).
Attraverso la tecnica della Model Order Reduction è possibile trasferire nell’ambiente di simulazione di Simplorer
modelli a parametri concentrati estratti da modelli agli elementi finiti realizzati tra gli altri in ANSYS Mechanical,
ANSYS Fluent e ANSYS ICEPack.
In Figura 5 viene sintetizzato lo stato dell’arte dell’integrazione di sistema in ANSYS.
3) Cosimulazione con tool esterni ad ANSYS
Programmi in C/C++, MATLAB® / Simulink®, ModelSim®,
QuestaSim® e Mathcad® possono essere integrati direttamente in Simplorer attraverso la tecnica della cosimulazione.
Questo permette una semplice e rapida implementazione di
modelli realizzati anche con software esterni al portafoglio dei
prodotti ANSYS.
La diretta integrazione dei modelli nel loro ambiente di simulazione evita la traduzione del modello, consente di risparmiare tempo
per la progettazione, e permette
la comunicazione e lo scambio di
informazioni tra diversi progettisti.
4) Analisi Statistiche e di
Ottimizzazione.
Optimetrics, tool embedded in
Simplorer, consente di effettuare
5) Tools di caratterizzazione di power devices.
Simplorer supporta strumenti e sistemi per la caratterizzazione di dispositivi di potenza quali
IGBT e converter AC/DC.
Per quanto riguarda l’analisi degli IGBT, Simplorer
fornisce due diversi metodi di caratterizzazione: dinamica
e mediata (dynamic and average). La caratterizzazione dinamica consente una maggiore precisione nel descrivere i
fenomeni di switching che avvengono in questi dispositivi, mentre la caratterizzazione average permette una modellazione del dispositivo tale da consentire tempi di simulazione più ridotti, fornendo comunque una stima delle
perdite medie durante le fasi di switching.
Entrambe le metodologie descritte leggono gli input necessari alla caratterizzazione del dispositivo direttamente
dai datasheet messi a disposizione dai fornitori.
Per quanto riguarda la definizione e la caratterizzazione di
dispositivi elettronici inoltre è possibile accedere in rete
(http://model.simplorer.com) ad una vasta libreria di modelli di componenti quali Diodi, MOFSFETs ed IGBTs.
In Figura 6 viene illustrato un esempio di simulazione multi dominio in ANSYS Simplorer.
Per maggiori informazioni
Emiliano D’Alessandro - EnginSoft
[email protected]
Fig. 6 - Simulazione elettro-termica di un commutatore IGBT in Simplorer.
ICEPAK 13.0: buone notizie per i
progettisti elettronici
I malfunzionamenti legati al surriscaldamento, le eccessive
sollecitazioni termiche sulla struttura e la gestione non ottimale della distribuzione dei flussi di calore sono problemi comuni nell’ambito della progettazione dei dispositivi elettronici. Tutti questi problemi possono essere studiati e risolti
utilizzando ANSYS Icepak.
Icepak è un codice di fluidodinamica computazionale robusto
e completo creato specificatamente per il controllo termico
dei dispositivi elettronici. Caratterizzato da un’interfaccia
estremamente intuitiva, permette di eseguire analisi termo
fluidodinamiche stazionarie e tempo transienti simulando
tutte le modalità di trasferimento del calore (conduzione,
convezione, radiazione e scambio termico coniugato).
Presente sul mercato da ormai più di dieci anni, Icepak è
giunto alla release 13.0 che ha aggiunto nuove funzionalità
in grado di aumentarne la facilità di utilizzo e di renderlo ancora più attraente al progettista elettronico.
Di seguito sono indicate le principali novità introdotte nella
versione corrente suddivise per aree tematiche:
Integrazione con ambiente Workbench
Il graduale inserimento di Icepak all’interno dell’ambiente di
lavoro Workbench, iniziato con la release 12.0, continua nella versione attuale.
In relazione alla fase di pre-processamento geometrico, sono
stati implementati in Design Modeler alcuni strumenti (riuniti nel gruppo dei tools denominato Electronics – vedi Figura
1) che permettono di semplificare entità geometriche anche
complesse e di convertirle direttamente in oggetti nativi di
Icepak con un notevole risparmio di tempo da parte dell’utente.
Fig. 1 - Strumenti di semplificazione e conversione geometrie in Design
Modeler: Electronics tools
Fig. 2 - Strumenti di semplificazione e conversione geometrie in Design
Modeler: Electronics tools
Per quanto riguarda la fase di post-processing, tutte le funzionalià del visualizzatore interno ad Icepak sono ora disponibili nel software unico di postprocessing di Workbench
(CFD-Post) che è uno strumento in generale più potente e in
grado di gestire griglie di calcolo anche di notevoli dimensioni (vedi Figura 2).
Sempre nell’ambito di una progressiva integrazione di Icepak
nell’ambiente di lavoro Workbench è da registrare il miglioramento dell’algoritmo di trasferimento del campo termico verso il solutore strutturale con una conseguente velocizzazione
dei tempi di calcolo per le analisi FSI 1way (vedi Figura 3).
Mesh
Il generatore di griglie di calcolo interno ad Icepak è stato
ulteriormente sviluppato al fine di automatizzare il processo
di meshing. Tra le nuove features ricordiamo:
• La nuova opzione di meshing multi level (2D zero Cut
Cell) permette un notevole risparmio di elementi di
griglia nel caso di modelli 2.5D ed è molto utile per la
modellazione delle tracce sulle printed circuit board (PCB)
(vedi Figura 4);
• il metodo di estrusione di griglia (Extruded Mesh) è stato
implementato al fine di controllare il numero di celle
posizionate nello spessore delle PCBs e dei Packages;
• L’utilizzo degli O-Grid per la generazione della griglia di
calcolo è stato ora esteso anche ad oggetti 2D
(precedentemente era applicato solo a entità geometriche
tridimensionali) con notevole beneficio sia della qualità
della griglia che della risoluzione dei boundary layer
termici;
• È ora possibile creare mesh non conformi per i singoli
componenti di un Assembly mettandoli a diretto contatto
tra di loro (Zero Slack Assembly). Questo miglioramento
nella gestione delle interfacce tra mesh porta ad una
notevole riduzione del numero degli elementi da usare per
discretizzare oggetti quali Heat sink, BGA etc. dove i
37
• Sono stati introdotti due nuovi modelli di radiazione: il
“surface to surface” e il “ray tracing”. Il primo modello è
semplice ed economico, adatto alla maggior parte delle
applicazioni con mezzi trasparenti. Il secondo modello è
molto più generale ed accurato ma dai costi
computazionali elevati. Da sottolineare inoltre il supporto
per il carico termico solare (compatibile con tutti i
modelli di radiazione) che permette di tenere in conto
della radiazione proveniente dall’ambiante esterno e del
suo orientamento nello spazio.
Fig. 3 - Trasferimento diretto dei dati da Icepak ad ANSYS Meshanical
Fig. 5 - Icepak permette di eseguire analisi termiche a varie scale dimensionali
Fig. 4 - Multi Level 2D Cut Cell Meshing
singoli componenti hanno dimensioni caratteristiche
molto differenti.
Modellazione
Uno dei punti di forza di Icepak è la possibilità di generare
modelli fisici rappresentativi dei singoli componenti elettronici da includere nella simulazione numerica quando il focus
dello studio non è a livello della componentistica (scala [m])
ma a livello di sistema (scala [m]) – vedi Figura 5. Questo
punto di forza è stato ulteriormente sviluppato con:
• Il miglioramento del sistema di caratterizzazione dei
packages elettronici denominato Delphi Extractor che
permette di creare in modo automatico una
rappresentazione RC (Resistiva Capacitiva) di packages
quali BGA, Exposed Die BGA e QFP (Figura 6);
• L’introduzione di una nuova macro per assistere nella
modellazione delle Heat Pipes (Figura
7).
La versione 13 è inoltre supportata per oggetti 2D quali Fans, Grilles, Walls e
Openings la geometria derivante da CAD.
Ciò permette di utilizzare forme geometriche realistiche anziché approssimazioni a
geometria poligonale per tali oggetti.
Solutore
Le novità fondamentali del solutore possono essere riassunte in 2 punti:
Fig. 6 - Caratterizzazione dei componenti: Delphi Extractor
• È ora possibile importare ed esportare oggetti networks
cioè modelli bidimensionali che rappresentare circuiti
integrati tramite file CSV/Excel.
Per concludere questa visione di insieme della principali novità introdotte con Icepak 13 è da segnalare la possibilità di
interagire in modo bidirezionale con
SIwave, software per il calcolo dell’integrità di segnale. Icepak può ora dialogare con SIwave fornendo mappe di temperatura e ricevendo campi di potenza.
Interazione che risulta fondamentale per
analisi dove le proprietà elettriche del dispositivo dipendono dalla temperatura.
Fig. 7 - Caratterizzazione dei componenti: Heat
Pipes
Per esempi, materiale e richieste di informazioni: Ing. Matteo Nobili - EnginSoft
[email protected]
Development of the Novel Opencell™
A completely new metal sandwich panel concept,
Opencell™, has been developed. Instead of the
conventional three constituent panel structure
(sheet/core/sheet), an integral cut-and-formed face sheet
and the core, and a solid face sheet are used. This concept
provides a reduction in the number of joining components
and thus manufacturing phases can be decreased for a
more cost-efficient process. An increased number of
design variables means potential for tailored properties.
Unlike many traditional metal sandwich panels, the
structure can have equal mechanical properties in the
longitudinal and transversal directions, and in specific
applications this concept provides stiffer solutions than
the conventional sandwich panels.
TECHNOLOGY REVIEW
Metal sandwich panels offer a number of outstanding
properties allowing the designer to develop light and
efficient structural configurations for a large variety of
applications. The most established type of all-metal
sandwich panels is the use of directional stiffeners
connected to each other using connection members
formed from one of the face sheets, i.e. without any
addition of the core material [4].
CONCEPT DEVELOPMENT
The motivation of the product development naturally is
increased performance. In principle, two approaches exist
to develop more efficient structures: either the
application of new materials or the use of novel structural
design – or a combination of these. Opencell™ idea itself
introduces a large number of design variables for tailored
properties. With Opencell™ one can build panels with
balanced transversal and longitudinal stiffness properties
and challenging panel shapes are possible (see Figure 1).
Within certain limits, panel height can be increased
without mass penalty. This means increased bending
stiffness offering potential for weight savings.
The initial concepts were not very efficient in terms of
structural performance and the project team focused on
the concept development. Different geometrical layouts
Fig. 1 - The Opencell™ structure can take the form of flat, single side curved and doubly side curved shapes.
(see Figure 2), providing a range of structural performance
between two solid face sheets, such as straight webs (Iand various types of packing patterns, were developed,
core), (rectangular) hollow sections (O-core), hat or
simulated using FEA, and evaluated for the proper
corrugated sheets (Vf/V-core), etc. [1].
understanding of their mechanical behavior.
In contrast to the previous ones, called calottes, formed
The purpose of the work was to make general comparative
indents to separate the panel face sheets provide more
analyses using a design study, for which a reference
isotropic properties. However the closed nature of calottes
application was adapted from an earlier sandwich project
limits their maximum depth (formability) [2, 3].
Another developing direction of
all-metal
sandwich
panel
technology is towards lattice
truss core structures. This has
evolved into a completely new
approach for a metal panel
structure
concept
called
Opencell™.
This
invention,
described in patent application
WO/2009/034226, includes a
panel structure wherein the core
structure is formed from face Fig. 2 - Some of the studied Opencell™ concepts. Three right-most solutions represent Opencell Delta™ concepts.
sheets that are mechanically All unit cells are in mutual scale, i.e. height of the panel is constant.
Table 1. Panel dimensions in the design studies.
[5]. This consisted of a beam-like supported 54 mm high
panel with a support span L of 2 m and a uniform pressure
load of 4800 Pa. A deflection constraint was set to L/300.
The objective was to meet this constraint with 4 mm steel
consumption divided between the two components.
39
In the optimization problem the objective
was to maximize specific stiffness of the
panel (inverse of the panel maximum
deflection divided by the total thickness of
the two sheets).
The optimization procedure was set up in modeFRONTIER,
the design optimization and process integration software
package of our choice. The design of experiments and
optimization algorithms provided in modeFRONTIER were
used to drive the Opencell™ towards our goals.
Thus modeFRONTIER created new designs by determining
input values for the variables which were fed to a fully
parametric FE model in ANSYS. Results for a single design
study are presented in the 4-D image of Figure 3.
Displacement results are presented as a function of the
three variables for the different designs.
For illustration, displacement results were
selected because they are not as abstract
as the specific stiffness. The unit cell
width is on the horizontal axis. The color
of the bubble indicates the total thickness
of the face sheets.
For example, cyan bubble (SUM_30…)
indicates that the total amount is 3.0
mm. The stiffest structure in terms of real
displacements naturally comes with the
highest amount of material. Therefore, red
bubbles (5.0 mm) are on top (least
negative values). In the study, the total
Fig. 3 - Bottom left: optimum layout for curved panel applications. Right: maximum displacement
results as a function of the unit cell width for a flat panel (H 75 mm, span 3 m). Top left: optimum amount of material was restricted to 5.0
layout for the flat panel.
mm. The diameter of the bubble indicates
the thickness of the plain sheet. The smaller the bubble is,
the thinner the sheet. Therefore, for this application, the
OPTIMIZATION
stiffest structure is obtained by maximizing the thickness
The next step in the project was to gather more
of the cut sheet. This is the trend particularly for flat
information about the type of applications for which the
panels with long support spans. Increased thickness on
Opencell Delta™ structure is appropriate and to determine
the cut sheet moves the neutral plane closer to the
the optimum cell configurations in the different
geometrical mid-plane and therefore, panels work better
applications. The design study was divided to flat and
in bending. For long span applications, bigger unit cell
curved panel applications. Three corresponding panel
size is preferable as it increases the amount of material at
heights were selected to represent different design groups
the surfaces. For short span applications, which are out(Table 1). Each design group was further on divided to
of-plane shear dominated, smaller unit cells are
three sub-groups determined by the span of the beam-like
preferable. It should be noted that the plain sheet should
panel. In case of flat panels, two opposite edges were
be rigid enough to avoid local deformation close to the
simply supported. For curved panels, also the longitudinal
supports or loading points.
translations were constrained on both edges. In both
applications, panels were loaded with a uniform pressure
Curved panels behave quite differently. They act
load of 4800 Pa.
essentially the same way as pressure vessels, where loads
are carried by membrane forces. Therefore, the in-plane
After the conceptual design studies it could be concluded
stiffness dominates the applications and the fewer cuts
that to achieve the best performance, certain geometrical
per unit area, the bigger the membrane area. The best
measures need to be driven towards the minimum or
specific stiffness is obtained with the combination of the
maximum allowed value. As a result, free design variables
thickest plain sheet and the thinnest cut sheet, and with
were limited to the choice of the unit cell width and the
the highest value of the unit cell width. Still, the cut
thickness combination of the two face sheets. Allowed
sheet should be thick enough so that local deformations
face sheet thicknesses for the two applications are
and stability are not a problem.
presented in Table 1.
A great performance improvement was achieved when the
Opencell Delta™ concept was established in which four
delta-shaped legs form the core. Also, it provided high
unit cell packing density and consequently, rather
homogenous structure.
Fig. 4 - The software solution provides panel key properties such as EI and GA. User can solve the panel deflection U under different boundary and loading
conditions. Stress recovery is made for a single unit cell with a separate model.
SOFTWARE SOLUTION
Opencell Delta™ simulation capabilities have been
integrated as a separate module in ESAComp, a software
tool for the analysis and design of layered composite
structures. The software module consists of three
components: geometry modeler, homogenization tool and
simulation tool.
The geometry modeler creates an FE mesh for a single unit
cell according to the user-defined parameters (e.g. panel
height, unit cell width, angle of the legs, etc.) and
provides basic functions for visualization of the geometry.
The homogenization tool calculates the basic properties of
the Opencell Delta™ panel. In the conceptual design
phase, designers would like to compare different
alternatives with some key properties, like panel axial
stiffness, bending stiffness, and shear stiffness, which are
derived internally. The panel properties can be used in
commercial FE codes to calculate deflections of flat and
curved panels with arbitrary shapes, boundary and loading
conditions. The homogenization approach is described in
detailed in [6].
The simulation tool integrated in ESAComp software
supports the analysis of flat panels (see Figure 4). The
ESAComp solution relies on Elmer solver [7]. Two types of
analyses are supported: static load response and analysis
of details that covers, for example, failure analysis.
CONCLUSIONS
The introduced Opencell Delta™ concept provides a brand
new way to construct metal sandwich panels. The concept
gives potential for cost savings in manufacturing due to
the reduced number of components and simplified
continuous manufacturing process. In specific
applications, increased mechanical performance can be
achieved even with less material when compared to
traditional metal sandwich panels, as could be shown
optimizing Opencell Delta™ panels with modeFRONTIER.
Both aspects are highly valued especially in
transportation applications. Opencell™ panels can be
formed in challenging shapes and they provide internal
space for wirings, piping and other equipment, which may
be required in the product. The presented software
solution provides an efficient way to perform panel
dimensioning. With a very limited effort one can reliably
estimate if the Opencell Delta™ concept brings benefits in
the specific application.
REFERENCES
[1] Säynäjäkangas, J. and Taulavuori, T. 2004. A review in
design and manufacturing of stainless steel sandwich
panels. Stainless Steel World, October, 2004. pp. 55 –
59
[2] Lohtander, M. & Varis J. P. A novel manufacturing
process for producing cell structures using a modern
turrett punch press. 17th ICPR (International
Conference of Production Research), 3 to 7 August,
2003. Blacksburg (VA), USA. 9 p.
[3] Larkiola, J., Martikainen, H., Pellikka, E. Simulations of
the forming and loading conditions of calotte panel
structures. Espoo, 2003. VTT Technical Research Centre
of Finland, report BTUO35-031181. 13 p. + 2 p. app.
[4] Patent application WO/2009/034226. 2009. Panel
structure. Outokumpu Oyj. Priority 11.09.2007, publ.
19.3.2009. 23 p.
[5] Gales, A., Sirén, M., Säynäjäkangas, J., Akdut, N., van
Hoecke, D. and Sánchez, R. 2007. Development of
lightweight trains and metro cars by using ultra-highstrength stainless steels. European Commission. Final
report EUR 22837. 266 p.
[6] Katajisto, H., Valente, A. and Mönicke, A. Designoptimisation of the innovative, high-performance
metal sandwich solution. 9th International Conference
on Sandwich Structures ICSS 9. California Institute of
Technology, Pasadena (CA), USA, 14 to 16 June, 2010.
[7] Elmer Models Manual, CSC - Scientific Computing Ltd.,
2007, Elmer web site www.csc.fi/elmer
HARRI KATAJISTO, ANDRÉ MÖNICKE
Componeering Inc., Itämerenkatu 8, FI-00180 Helsinki,
Finland
ANTONIO VALENTE
PLY Engenharia, Lda, Largo dos Fornos 1, PT-2770-067
Paço de Arcos, Portugal
41
Componenti forgiati di qualità
necessitano di un approccio CAE
integrato – esperienze di simulazione di
processo nel campo Energia e Nucleare
Acciaieria - processo di colata
Il processo di colata di lingotti è caratterizzato da una serie
di parametri molto complessi, che determinano la qualità del
prodotto finale. La composizione della lega è uno degli
aspetti più importanti, ma lo sono anche le modalità di colata (velocità di colata, utilizzo di polveri isolanti, …) ed i
materiali utilizzati per la lingottiera. Tutti questi aspetti sono tenuti in conto dai software di simulazione, che possono
dare delle utili informazioni su quello che succede nella fase
di riempimento dello stampo e di solidificazione del metallo.
Software specifici in questo ambito (MAGMAsoft di Magma
GmbH ad esempio) riescono a valutare, oltre ai ritiri in soli-
Fig. 1 – MAGMASOFT – simulazione del riempimento di un lingotto.
Fig. 2 – MAGMASOFT – simulazione della solidificazione di un lingotto.
Fig. 3 – MAGMASOFT – distribuzione di temperature in una lingottiera.
Fig. 4 – MAGMASOFT – Difetti: macro ritiri, micro ritiri, moti convettivi,
segregazioni.
SIMULAZIONE DI PROCESSO NEL CAMPO ENERGIA E NUCLEARE
I processi di forgiatura a stampi aperti (open-die) e di laminazione circolare (ring-rolling) sono in grado di produrre pezzi di grosse dimensioni in acciaio, il più possibile privi di porosità e con la massima omogeneità nelle caratteristiche
meccaniche. Tali specifiche sono richieste nei settori meccanico-siderurgico (alberi pignone, pignoni, ruote pignone, alberi eccentrici, terminali e manicotti, …), petrol-chimico
(corpi valvola, tubi, B.O.P., …), navale (alberi intermedi, alberi pinna ed alberi timone, …) e dell’energia (alberi turbina, alberi ventilatore, alberi per eolico, generatori quadripolari, …). In particolare in questo ultimo ambito, i componenti necessari per la costruzione di centrali nucleari devono
soddisfare delle normative molto restrittive in grado di garantire le prestazioni del manufatto dopo molti anni di utilizzo in condizioni severe di contatto con agenti aggressivi e
sottoposti ad irraggiamento. Si cerca quindi di produrre particolari con meno discontinuità (porosità, inclusioni, segregazioni, …) possibile e che possano essere assemblati limitando al minimo le saldature. Lo sviluppo integrato (la design chain) parte della colata dell’acciaio in acciaieria in una
forma opportuna (lingotti, barre, blumi, altre forme), per proseguire con il trasferimento in forgia, dove il lingotto viene
controllato, trattato termicamente e quindi lavorato alla
pressa e/o al laminatoio. Il trattamento termico e le lavorazioni meccaniche di sgrossatura e di finitura sono le fasi conclusive per l’ottenimento del pezzo finito. Per ognuna di queste fasi esistono degli strumenti di simulazione dedicati e
verticalizzati che consentono di simulare accuratamente le
condizioni al contorno della fase in esame allo scopo di prevedere e ottimizzare la qualità del componente, grazie ad una
migliore comprensione dell’influenza dei parametri di processo. L’approccio viene applicato e descritto successivamente
nel caso di un lingotto in acciaio.
una uniformità di temperatura tra cuore e superficie.
La simulazione del riscaldo in forno (fig. 5) può essere effettuata con software come Forge, dove può
essere specificata una curva dell’atmosfera del forno
e le temperature del lingotto possono essere monitorate attraverso dei sensori. L’utilizzo dell’ottimizzatore integrato in Forge può essere utile per calibrare i tempi di permanenza in forno: grazie a questo strumento, nel caso specifico di un lingotto da
Fig. 5 – Forge - riscaldo in forno lingotto da 40t – temperature a cuore ed a superficie.
40t, si è compreso come il tempo di permanenza alla rima temperatura deva essere aumentato da 16 a
24h, mentre alla massima temperatura si possono risparmiadificazione, anche la formazione di porosità, la segregazione
re ben 12h.
dei vari elementi, la presenza di cricche a caldo, … (Figure
1, 2, 3, 4).
Forgiatura – processi di deformazione open-die
Al termine della prima fase del processo produttivo, ci si poIl processo di forgiatura è caratterizzato dalla presenza di
ne come obiettivo quello di trasferire le proprietà microstrutdue elementi fondamentali: il manipolatore, che tiene il pezturali e gli eventuali difetti alla fase successiva come avviezo in posizione e ne guida gli spostamenti e le rotazioni, la
ne nella sequenza reale. L’ormai pluriennale esperienza matupressa, che deforma il pezzo con diversi colpi e passate. La
rata in EnginSoft sia nel CAE che nel processo manifatturiero
forma finale viene ottenuta infatti attraverso una serie di deha permesso lo sviluppo di algoritmi specifici che agevolano
formazioni localizzate sotto le mazze, con tempi di diversi
il dialogo fra strumenti software commerciali di diversa natuminuti che comportano un raffreddamento dell’acciaio e la
ra e storia.
necessità di prevedere, soprattutto per pezzi di grosse dimensioni, delle ricalde in forno anche di diverse ore, per riForgiatura – processo di riscaldo del lingotto
portare il pezzo alla temperatura di lavorazione. Le difficoltà
Il lingotto prodotto in acciaieria viene trasportato alla forgia,
principali nella simulazione di questo processo sono la necesdove viene inizialmente riscaldato in forno. Questo processo
sità di automatizzare la sequenza degli afferraggi da parte
non è così semplice come sembra, in quanto bisogna adottadei manipolatori, la sequenza dei colpi e delle passate, con
re degli accorgimenti in modo da garantire un riscaldo unile corrette rotazioni e traslazioni del pezzo e/o delle mazze.
forme cuore-superficie, guidando nel contempo le trasformaFondamentale è la corretta definizione del
materiale in termini di curve di deformazione a caldo e dalla corretta definizione delle caratteristiche della pressa idraulica utilizzata. Il software Forge è stato sviluppato
in questi termini grazie all’apporto dei molti utilizzatori francesi che producono nel
Fig. 6 – Forge – possibili movimenti impostabili per ogni colpo/passata ed esempio blumatura.
campo dell’energia: la sequenza di colpi e
passate può essere definita con precisione
zioni che avvengono nell’acciaio aumentando la temperatura.
(fig. 6), indicando quando entrano in funzione i manipolatoLe dimensioni dei lingotti sono considerevoli, quindi bisogna
ri. Per ciascuno di essi si può specificare la zona di presa o e
modulare il forno in modo tale che l’acciaio venga portato
l’eventuale rigidezza degli afferraggi, che possono arretrare
gradualmente ad una temperatura attorno ai 700-800°C, che
alla spinta del materiale. La geometria delle mazze e del lindeve essere mantenuta per qualche tempo in modo da rendegotto di partenza vengono infine importate da CAD (formati
re omogeneo il cambio di fase e non creare eccessivi gradien.stl o .step).
ti termici cuore - superficie, dopodiché si può procedere fino
Durante la simulazione si può valutare come viene indotta la
alla temperatura di forgia di 1150-1200°C, fino ad ottenere
deformazione del materiale: quando la pressa esaurisce
Fig. 7 – Forge – ricalcatura, blumatura, stondatura spigoli, ricalcatura di testa e martellatura.
43
la posizione nel lingotto di partenza, come è mostrato in fig.
9. L’utilità di questo metodo consiste nella identificazione
degli istanti in cui i difetti si generano e le relative cause per
agevolare il tecnico nella ricerca della soluzione appropriata
e efficace.
l’energia, la mazza si arresta e si passa al colpo successivo.
Se il materiale è troppo freddo non si raggiungono le altezze
di ricalcatura/blumatura desiderate, perciò dall’analisi delle
curve di discesa si può capire quando sia necessario sospendere la lavorazione per riportare in temperatura il pezzo.
Possono essere simulate pressoché tutte le lavorazioni che
vengono effettuate in forgia: ricalcatura con mazza piana o
con bocca, blumatura a stampi piani, curvi o sagomati, stondatura degli spigoli, ricalcature di testa (Fig. 7). Partendo da
barre o blumi è possibile utilizzare solo due mazze verticali o
macchine più complesse con 4 mazze, per il processo di martellatura rotante, o valutare in virtuale macchinari definiti
solo sulla carta.
Fig. 9 – Forge – valutazione a ritroso posizione difetti attraverso l’uso di sensori.
La simulazione viene utilizzata anche per valutare se la deformazione è in grado di compattare a sufficienza il materiale, partendo eventualmente da una distribuzione di porosità
proveniente dalla simulazione di colata del lingotto, come è
mostrato in Fig. 8.
Gli eventuali difetti nel forgiato sono ovviamente oggetti di
indagine e lo studio può essere effettuato anche a ritroso,
ovvero definendo la posizione del difetto rilevato nel pezzo
finito e seguendone il movimento “a marcia indietro” fino al-
Fig. 10 – processo di ottenimento di anelli a sezione rettangolare da laminare
In questo caso si effettuano delle analisi 2D molto rapide, simulando le fasi di ricalcatura, sagomatura, punzonatura e foratura, come mostrato nella fig. 11 per un anello sagomato.
La funzione di “chaining” consente impostare, calcolare ed
analizzare in sequenza tutte le operazioni, trasferendo i risultati da una operazione alla successiva, fino all’ultima azione
di tranciatura, nella quale si abilita la funzione di danneggiamento per seguire la separazione del fondo per effetto del
punzone di tranciatura.
Volendo rimanere nel campo della produzione di componenti
per il settore nucleare, un altro processo comunemente utilizzato per l’allargamento degli anelli è la bigornatura: l’anello ottenuto come sopra illustrato, di sezione rettangolare,
viene caricato su un mandrino ed una
mazza che ne provoca la deformazione
localizzata. La rotazione del mandrino
tra un colpo ed il successivo consente
di ottenere un allargamento graduale
dell’anello, preservandone la lunghezza
(Figura 12).
Forgiatura – processi di laminazione
circolare
L’anello prodotto con le fasi sopra descritte può quindi essere laminato, per ottenere le dimensioni (allargamento) e/o la forma desiderata (sagomatura del
profilo). I laminatoi, che possono essere di diverso tipo, sono costituiti generalmente da un rullo principale che induce
la rotazione, da un mandrino, che spinge il materiale verso il
rullo e da eventuali coni, che guidano l’altezza del profilo.
Tutti questi oggetti possono essere piani o sagomati. La simulazione di questo specifico processo risulta molto complessa per la limitata area di contatto tra mandrino, anello e
rullo, nella quale si concentra la massima deformazione e per
la cinematica guidata dall’allargamento dell’anello. L’elevato
Fig. 8 – Forge - chiusura delle porosità di colata con il processo di forgiatura.
Risulta quindi ovvia la possibilità di calibrazione virtuale delle fasi di forgiatura necessarie per l’ottenimento di anelli a
sezione rettangolare o sagomati, che poi possono essere laminati (fig. 10).
Fig. 11 – Forge – 2D ricalcatura, punzonatura e tranciatura fondo per un anello sagomato.
Fig. 12 – Forge – bigornatura anello.
i tipici difetti di forma di questo processo, presenti soprattutto per pezzi sagomati: fish-tailing, mancanze di profilo,
rigetti di materiale.
Forgiatura – trattamento termico
Per tutte le tipologie di pezzi sopra tratFig. 13 – Forge – simulazione processo di laminazione circolare anello rettangolare e sagomato.
tate, dopo la fase di deformazione è
sempre presente il trattamento termico
per migliorare le caratteristiche meccaniche dell’acciaio. Il processo, che può
essere anche molto articolato, si compone di un riscaldamento in forno alla temperatura di austenitizzazione ed una
Fig. 14 – Forge – simulazione trattamento termico: temperatura, % martensite e durezza HV.
successiva immersione in un bagno di
tempra, che induce delle trasformazioni
microstrutturali nell’acciaio, modificando le fasi presenti. A seconda della drasticità dello scambio termico, si vanno a
formare ferrite, perlite, bainite e, nella
zone dove massimo è il gradiente, martensite. Nello specifico, la trasformazione martensitica è una trasformazione
esotermica ed induce una espansione
Fig. 15 – Forge – simulazione fase di immersione dell’anello in bagno di tempra.
della struttura cristallina, che può provocare una distorsione del pezzo. Anche
numero di giri infine rende il numero di calcoli da effettuare
per questa operazione è possibile utilizzare la simulazione,
molto elevato con una mesh adattiva che si aggiorna in parcon il software Forge, per valutare, al variare del percorso di
ticolare nelle zone di contatto. In tal caso le architetture
tempra e della forma del pezzo la formazione delle varie fasi,
hardware con calcolo parallelo multi-core o multi-processore
in funzione del raffreddamento imposto alle varie zone, per
(cluster) permettono di ottenere dei risultati sufficientemenconfronto con le curve TTT del materiale. Viene infatti effette accurati tempi ragionevoli. Nello specifico della definiziotuato un calcolo termico-meccanico-metallurgico accoppiato,
ne delle cinematiche del mandrino e dei coni è possibile guigrazie al quale si ottengono le fasi e la conseguente durezza
dare gli stampi mediante le stesse curve di laminazione che
finale del pezzo (fig. 14).
l’operatore imposta sul software del laminatoio, riproducendo quindi in virtuale il comportamento della macchina reale.
Recentemente il modello di calcolo è stato migliorato per tener conto di parametri di processo quali ad esempio la duraL’analisi del comportamento del materiale tra mandrino e rulta della fase di immersione nel bagno di tempra e l’effetto
lo consente di modificare la curva di laminazione e risolvere
sulla tempra del pezzo, come è mostrato in fig. 15.
45
Fig. 15 – Forge – simulazione fase di immersione dell’anello in bagno di tempra.
Una volta valutate tutte le singole fasi di produzione di un
componente, dalla colata dell’acciaio, alla deformazione, alla
tempra ed alle lavorazioni meccaniche, è possibile infine utilizzare i risultati ottenuti (distorsioni di forma, stress residui,
proprietà meccaniche, difetti, …) per effettuare delle analisi strutturali o fluidodinamiche, nelle quali valutare le prestazioni in esercizio del componente. Nell’immagine seguente è
mostrato come l’introduzione degli stress residui e delle proprietà meccaniche come condizioni iniziali per l’analisi strutturale modifichi in modo rilevante le caratteristiche meccaniche di un corpo valvola sollecitato in esercizio.
Gli strumenti adatti e le competenze adeguate determinano
un binomio vincente per lo studio e la progettazione di componenti High Tech forgiati per il settore energetico e in particolare quella nucleare.
EnginSoft ha estese competenze nella simulazione di processo, derivanti da oltre 15 anni di esperienza a diretto contatto con questo tipo di problematiche del mondo industriale.
Conclusioni
La presente panoramica ha evidenziato come oggi sia possibile simulare tutte le operazioni necessarie alla produzione di
un particolare in acciaio di grosse dimensioni, partendo dalla colata del metallo nel lingotto, alla successiva lavorazione
di forgiatura o di laminazione, al trattamento termico.
Aspetto saliente è la possibilità con questi diversi strumenti
di valutare tutta la design-chain, in modo da essere in grado
di comprendere le cause di un problema andando a ritroso
lungo tutti i vari passaggi di produzione.
SOCIETÀ DELLE FUCINE – THISSEN KRUPP
Società delle Fucine ha deciso di intraprendere la
collaborazione con EnginSoft e dotarsi di strumenti di
simulazione numerica del processo di fucinatura, scegliendo in
particolare il software Forge nella versione parallela
multiprocessore. La competenza e disponibilità dei tecnici di
EnginSoft è risultata fondamentale per la rapida introduzione
dei nostri parametri di processo e la taratura dei modelli
numerici di fucinatura a stampi aperti che ha consentito di
raggiungere simulazioni aderenti alla realtà in tempi molto
rapidi. L'ing. Roberto Caldarelli, responsabile della
preventivazione e della progettazione delle sequenze di
produzione dichiara: “La scelta è caduta su questo programma
grazie alla estrema flessibilità nella definizione delle
cinematiche: tramite semplici istruzioni è possibile impostare
le passate ed i singoli colpi, indicando il tempo di pausa tra
un colpo ed il successivo e tutte le movimentazioni effettuate
dal manipolatore per posizionare correttamente il pezzo sotto
la pressa. Questi aspetti sono essenziali, assieme a risultati
che abbiamo verificato essere molto precisi, per poter
utilizzare Forge per prevenire possibili problemi di
deformazione del pezzo sotto la pressa, adottando opportune
modifiche dei cicli di stampaggio.“ “Prevediamo di utilizzare
le simulazioni in modo via via sempre più sistematico per i
nuovi pezzi prodotti e di estendere il suo utilizzo alle fasi di
riscaldamento in forno, per prevedere tempi di riscaldo e
dilatazioni e per il successivo processo di tempra, per valutare
le deformazioni relative alla trasformazione martensitica,
grazie alla possibilità di simulare le trasformazioni
microstrutturali”. Per ultimo si cercherà un collegamento con i
risultati ottenuti dalla simulazione della colata dei lingotti, in
modo da tener conto delle caratteristiche proprie del lingotto
di partenza e simulare tutto il processo produttivo.
FORGIATURA MAMÈ
Abbiamo fondato il CRS (Centro di Ricerca e Sviluppo) con
l'obiettivo di sviluppare il nostro know-how e migliorare le
conoscenze sui nostri prodotti e sul processo produttivo.
L'acquisto di FORGE il software di simulazione del processo di
forgiatura e trattamento termico ha lo scopo di aiutare il CRS
nella creazione di know-how. Grazie a questo software è
possibile quindi analizzare il processo nel dettaglio,
ottimizzando le fasi di fabbricazione, la qualità dei prodotti e
quindi la riduzione dei costi e dei tempi - ciclo. L'ambizione
dell'azienda è quella di riuscire ad offrire ai propri clienti un
concreto strumento di cooperazione nella fase di
progettazione dei prodotti, analizzando e simulando le
caratteristiche che più soddisfano i requisiti che il forgiato
deve possedere in funzione della sua destinazione d'uso.
L'utilizzo di Forge rappresenta il punto più importante
dell'attività del CRS: permetterà di acquisire una conoscenza
oggettiva, di tipo scientifico-ingegneristico. Non più soltanto
empirica e legata quindi solo all'esperienza personale di chi fa
parte dell'azienda.
Per informazioni, rivolgersi a:
ing. Marcello Gabrielli – EnginSoft
[email protected]
Landi Renzo: the global leader in the
sector of components
and LPG and CNG fuel systems
Based in Cavriago (Reggio Emilia
- Italy), with more than 50 years
experience in the sector, Landi
Renzo is distinguished by a
sustained revenue growth, a
listing in the STAR segment of
the Italian stock exchange, and the extent of its
international operations, with a presence in over 50
countries.
The Landi Renzo Company was established in 1954 when
Renzo Landi and his wife Giovannina Domenichini founded
Officine Meccaniche Renzo Landi, at the time the only
manufacturer of mixers specifically designed for all kinds of
vehicles.
Landi Renzo S.p.A. is
now a global leader in
the
sector
of
components and LPG
and CNG fuel systems
for motor vehicles,
serving more than
30% of the market of alternative automotive fuel systems
and components. It is a preferred supplier by a growing
number of worldwide brands like Daimler Chrysler, Fiat, Opel,
PSA, Renault, Volkswagen, and more recently Toyota.
Landi Renzo S.p.A. Research and Development Centre is
currently the only one in its field to use advanced
technologies that allow creating and developing modern
systems to convert vehicle fuel systems to LPG and CNG.
Visit the website on: www.landi.it
modeFRONTIER in LandiRenzo
“The first project with modeFRONTIER®, a product of ESTECO
srl, dates back to 2008, when we performed an optimization
of the new Electronic Pressure Regulator (EPR) - says
Ferdinando Ciardiello, Research & Development Modelling
Manager at Landi. “Ercole Sangregorio, current EPR Project
Manager, - continues Ciardello - built-up a two steps
development: at first, leveraging on experimental test data
available in our in-house facilities, modeFRONTIER calibrated
a numerical model of the EPR. We obtained a very precise 1D
model, able to predict well and quickly the system’s behavior,
the steady-state and the transient in different possible
configurations. Afterwards, modeFRONTIER was used as a
process integrator and a multi-objective optimizer,
connecting different software tools to build a truly and
multi-disciplinary virtual bench, with mechanical, pneumatic
and control system models, and finding overall optimal
configurations. In this way, we
were able to minimize pressure
oscillations in the control
volume and to get an optimal
and robust EPR configuration in
just few weeks”. “Moreover, we
expanded the concept to 3D
fluid-dynamics
design,
particularly with the ANSYS
Workbench direct node in
modeFRONTIER, resulting in
scheduled
3D
simulation
campaigns during night time
and weekends. It proved to be a very efficient approach,
based on the state-of-the-art Design Of Experiment available
in modeFRONTIER.”
Why modeFRONTIER and EnginSoft
“Computer-Aided Engineering has always been a key success
factor for our growth”, says Viliam Alberini, Leader of the
Components Division, “and EnginSoft has been supporting
our demands well for years. Adding modeFRONTIER to our
software chain in 2008 has been a winning move for more
than one reason: with modeFRONTIER our approach to
product concept has become more systematic and now allows
us to evaluate more alternatives and take into account the
effects of more design variables. This translates into value to
our customers: critical factors are understood and handled
much earlier in the process and the design results more
robust in a shorter time. modeFRONTIER has also improved
the predictive power of our numerical models by feeding
them with lab testing results. This philosophy has reduced
development times and costs, and our team can cater to
customer demands and discuss specifications with them more
efficiently”.
47
The CAD-CAM Cooperation in Nissan
Achieved by ASFALIS
Manufacturing companies are increasingly tending to
centralize the management of their 3D product data. This
requires moving from segmented 3D CAD data conversion
and communication paths to a single integrated system.
Such a system must be able to correctly translate product
data from one CAD system to another and also be able to
prepare the data for other uses, such as FEA and CAM.
However, these tasks are not always done correctly or
adequately due to the significant difficulties in handling
mismatches between various software systems. Though
this is a difficult undertaking, Nissan Motor Company –
the well-known Japanese automobile manufacturer – has
successfully built a reliable system for conversion and
distribution of their 3D product data to be used companywide for all CAD-CAM operations.
At Nissan, the control and delivery systems had used many
3D tools in production technology, and the level of data
quality had differed from tool
to tool. This difference in
quality frequently disrupted
the
accuracy
of
data
translation. To solve this
problem, Nissan launched a
new project to shift to a
totally
new
translation
workflow, while changing its
standard CAD system from Ideas to NX.
On this project, Nissan chose
‘ASFALIS’, one of the products
of Elysium - a Japanese
provider
of
3D
interoperability solutions - to
consolidate the company-wide data conversion system in
order to achieve high accuracy and great stability of
performance. ASFALIS helps users establish a large-scale
and flexible system to automatically operate CAD-to-CAD
conversion or other optimization. It has been introduced
among many Japanese major automobile manufacturers
for their CAD conversion.
“We are replacing all the 3D translators in production
engineering with Elysium’s ASFALIS, which controls all the
3D data translation and distribution processes in Nissan,”
said Katsuro Fujitani, senior manager of the
manufacturing and SCM system department in global IS
division (as of 2010). He continued, “With its preeminent
translation performance, more than 99.9 percent of the
data can be converted without error.” ASFALIS adapters
are ready for all the possible translation patterns, which
allow the Nissan staff to utilize any type of CAD data. In
fact, they translate 3D data between INCAM* and several
CAD systems such as I-deas, NX and DELMIA. Even large
amounts of data are automatically converted and delivered
to predetermined destinations. It is also able to control
concurrently running file translation processes. Because
the ASFALIS-based system is integrated to the intranet
and connected with ‘Teamcenter’, the master PDM, Nissan
staff in domestic branches are able to access ASFALIS to
execute translations. The results of translations are
automatically delivered in a specified format to another
branch.
Even though different paths are needed between approved
data and data under consideration, users merely have to
change settings. Once configured, ASFALIS automatically
translates data and distributes results, whose quality is
admirable and stable. Elysium’s reliable 3D data
translation and distribution system has improved the
efficiency at every step of processes throughout the
product lifecycle management (PLM) in Nissan.
* INCAM is the in-house CAM system in Nissan.
For more information, please visit the ELYSIUM website:
http://www.elysium-global.com
For information on Elysium products in Italy, please contact:
Giorgio Buccilli at EnginSoft, [email protected]
CAE-based tablet design
It actually is an extremely important requirement today to
develop tablets that are easy to swallow, both from a
compliance and a usability point of view. Until recently, no
quantitative research on the correlation between shape of tablet
and ease of swallowing has been made. It was Mr. Hideaki Sato
of ASAHI BREWERIES, LTD. who began to investigate the shape
of tablets for ease of swallowing, using sensitivity engineering
and optimization methods to develop the most suitable shape.
Mr. Hideaki Sato evaluated the “tablet shape/hardness” and the
“pressure resistance” of the tablet machine pestle using the FEM
simulation software ANSYS.
Supported by
Economic growth has provided us with many rewards including a
wealthy and comfortable society. At the same time though, we
are facing problems that occur with an aging population and an
increase in lifestyle diseases. Even in Japan, the country with
the highest life expectancy, health problems linked to lifestyle
and age are evident. While in Europe, Japanese cuisine has
become quite popular in the last decade, also for supporting a
healthy diet and for curing disorders linked to an excessive
lifestyle, in Japan a trend of eating more “fast” and less
Japanese food can be witnessed. The consequences are increases
in bad dietary habits and lifestyle diseases. Both have led to
more frequent and longer sicknesses and to shortened life
expectancy. In a modern society like this, pharmaceuticals are
more and more in demand to offer supplements that can
effectively treat our increasing health disorders and thus
improve the quality of our lives.
ASAHI BREWERIES GROUP is one of the largest food
manufacturers in Japan. The Group mainly produces alcoholic
beverages, but also focuses on the research and development of
various supplements for the food production part of their
business. Some of these supplements are designed for
compensating the lack of a healthy nutrition, such as vitamins
and minerals that tend to be insufficient in our modern diet.
Some of these supplements include beer yeast for which the
ASAHI BREWERIES GROUP has become world-famous. The Group’s
supplements are of the highest quality and hence are products
that we can trust.
Pharmaceuticals and supplements are available in many forms,
such as tablets, granulates, hard and soft capsules, jellies or
syrups. Tablets are the most common today, and they come in
many different shapes, colors and flavors. People sometimes find
it difficult to swallow tablets because they must be taken
without chewing and are usually washed down with hot or cold
water (except for chewable tablets).
Study of the tablet’s shape for ease of swallowing
To review the correlation between tablet diameter, radius of
curvature, thickness and ease of swallowing of the most typical
circular tablets, the following steps were carried out by using a
sensory evaluation technology based on the experience of food
development and response surface methods.
Step 1: Preparing tablets
36 different shapes of tablets made from microcrystalline
cellulose and calcium stearate were prepared with all the
possible combinations of tablet diameter (6mm, 7mm, 8mm and
9mm), radius of curvature (6mm, 9mm and 12mm) and thickness
(3 values from 2.5mm to 6.5mm).
Fig. 1 - The shape of the circular tablet
Step 2: Sensory evaluation
The participants were 10 healthy men and women who took
tablets from Step 1 with a glass of water every 30 minutes in
random order. With the sensory evaluation, the ease of
swallowing was rated on a 5 level score.
Fig. 2 - The response surface of tablet diameter, radius of curvature and ease
of swallowing
Step 3: Analysis of sensory evaluation result
Based on the results of Step 2, the response surface of the tablet
diameter, radius of curvature and ease of swallowing was
established by spline interpolation connecting each data point.
This was done for actual ease of swallowing and for apparent
ease of swallowing.
The result shows that it is easier to swallow when both the
diameter and the radius of curvature are smaller with the
smallest diameter and radius of curvature being the easiest when
the thickness is 3.5mm. However, the best score for swallowing
in cases where thickness exceeds 3.5mm is when the diameter is
7mm, not the lowest value 6mm. This way, it became clear that
the smaller diameter is not always better for swallowing.
Moreover, it is important to consider the most appropriate
diameter based on the radius of curvature and the thickness.
Regarding the apparent ease of swallowing, the result was
different from the result of the actual ease of swallowing. The
participants felt that smaller diameters and smaller radiuses of
curvature are generally better. Additionally, the best shape for
swallowing based on each volume was specialized. This research
revealed the relation between tablet shape and ease of
swallowing.
Considering the fact that it is indeed difficult to change
pharmaceutical diameters in Japan, the conclusion was that the
most appropriate solution would be to reduce the radius of
curvature (i.e. to make the shape round).
However reducing the radius of curvature size entails the
problem of decreased durability of the tablet and the die (a part
of the tablet machine pestle). To overcome this, ANSYS was used
for the stress simulation of the arbitrarily-shaped tablet and
tablet machine pestle.
Stress simulation for the arbitrarily-shaped tablet
Typically, in the pharmaceutical and food industries, the tablet
strength is evaluated by a stress test to examine the fracture
load under the unidirectional load of the tablet. This is called
“Tablet Hardness”. To predict this as accurately as possible, CAE
simulations were performed. We should mention here that this
was the first time that a CAE approach has been applied in these
industries. In fact, tablet strength evaluations are very
challenging, as tablets are made of compressed formations of
powdered substances and unlike mechanical structures, the
shape and Young’s modulus are different and dependent on the
pressure loads.
Step1: Simulation under the assumption of a constant Young
moduleus
As a first step, the reaction force of the tablet, a 1/8
symmetrical segment model, was calculated under enforced
displacement. In this simulation, it was assumed that the
tablet’s Young Modules was constant, and an adequate material
property was defined for the model. It was done this way
because 3 different shapes of tablets made by the same pressure
load had almost the same volume (density), and the prediction
was that the Young Modules would be constant. However, there
was a divergence between the simulation results and the test
49
results under the same conditions. So, it became obvious that
applicable accuracy cannot be expected under the assumption
that the Young Modules is constant.
Fig. 3 - 1/8 model of the tablet and analysis condition
Step2: Simulation with the Young Module defined by the reaction
force on the pestle
This new approach was applied to gain realistic values for the
tablet’s Young’s Modulus. The stress simulation of the tablet
machine pestle was performed to obtain the reaction force on
the pestle head when tableting, and then to verify the
distribution of the reaction force as the distribution of the
tablet’s Young Modulus by transcribing it to the tablet model.
Fig. 4 - The tablet machine pestle and the area of the simulation
Fig. 5 - 2D symmetrical model for the simulation
In order to determine the reaction force on the contact area, a
stress simulation using the 2D symmetrical model shown in
Fig.5, was performed. The model was made from chrome-nickel
and a load of 20kN was applied to the upper region. The
distribution of the reaction force was obtained by the simulation
illustrated in Fig.6.
The reaction force was then transcribed to the tablet model for
its own stress simulation. At the same time, the average reaction
force for each divided region (2 parts or 4 parts) was transcribed
Fig. 9 shows the 3 different contour plots of the stress
simulation for the tablet with a diameter of 8mm and a radius
of curvature of 15mm. These are the results when the Young
Modulus is assumed to be constant, divided into 2 parts and
divided into 4 parts, respectively from left to right.
The new approach to transcribe the reaction force on another
model of the analysis model was applicable in this case. However
further considerations regarding the applicable range (e.g.
powder property, tablet machine type and tablet machining
conditions) will become necessary in the future.
Fig. 6 - The reaction force distribution on the pestle head
Fig. 7 - Young Module transcription to the tablet model
Fig. 8 - Relation between tablet hardness and reaction force
to the similarly divided region of the tablet model (the
transcription model of SATO-MIURA).
The result of the ANSYS simulation was consistent with the
experimental result, and it led to suitable results with practical
accuracy.
Stress simulation for the arbitrarily-shaped tablet machine
pestle
The tablet machine is in operation all day to compress powder
instantaneously with hundreds or thousands of kgf of pressure.
A lot of stress occurs on the machine and sometimes this causes
breakage. When reducing the tablet curvature size, the pestle
head will be sharpened and the load capacity of the pestle will
drop to a lower level. In the past, the load capacity of the pestle
used to be based on the tablet machine manufacturer’s
experimental rules. To predict the load capacity more accurately,
an ANSYS simulation of the tablet machine was performed. A 2D
axisymmetric model was prepared and the contact element
between the pestle and the tablet was defined to represent the
pestle sliding slightly on the tablet during the powder
Fig. 10 - Analysis condition
Young Module of the pestle:
166,100Mpa
Poisson ratio of the pestle: 0.3
Acceptable stress value of
metallic material of the pestle:
2,172Mpa
Tablet diameter: 6.0mm and
8.0mm
Land: 0.1mm
Contact stiffness coefficient of
the pestle and the tablet: 5.0
compression phase. The surface of
the tablet was defined as rigid. The
analysis condition is shown in Fig.
10. In this simulation, the
calculation was repeated until the
stress value inside the pestle reached the allowable stress value
of 2,172Mpa in order to know the load capacity.
Fig. 11 shows the area which might break. This
corresponds exactly with the tablet machine
manufacturer’s experimental rule. Hence we can
conclude that the CAE simulation for the tablet
machine is valid.
Fig. 9 - the maximum principle stress of the tablet with 8mm tablet diameter and 15mm radius of
curvature
The new approach of using CAE received a
great response from industry
Today, CAE is the standard tool of machine
design manufacturers and many examples,
Fig. 11 - Contour plot of the equivalent stress
Comments from Mr. Sato of ASAHI BREWERIES, LTD.
(Share the Kando.*)
In today’s food industries, we only find a few examples
for CAE- (and even fewer for FEM-) based product
development. For the work described in this article, we
applied ANSYS to evaluate our tablet design, and this
attempt provided us with a lot of new and useful
information. The response surface for the ease of
swallowing has high prediction accuracy, this is why it is
now used for product development in the ASAHI
BREWERIES GROUP. Regarding the transcription model,
the idea to consider the reaction force on the pestle as
the tablet’s Young Module was a complete breakthrough.
For the use of the approach in the future, we would like
to make a decision on the applicable range of the
theoretical model based on the powdered material and
the working conditions of the tablet machine.
We are no CAE specialists, so to us simulation is just a
tool and not our main objective. It is necessary to
cooperate with the CAE vendors for those simulation
cases which cannot be solved by ourselves. In such
situations, it is very important to deliver our analysis
results and requirements to the CAE vendors as sufficient
engineering knowledge and analytical thinking are
indispensable. We expect from the CAE vendors that they
don’t stick to their own technologies and simulation
results, and that they provide flexible services. There are
cases where – after sufficient communications and
exchange of information - we find out that no use of CAE
simulation is necessary.
I am very pleased that Mr. Miura of Cybernet Systems has
always responded quickly to my requests, and that he is a
reliable partner. I do believe that the best solutions come
from human communication, not from automatic
computational calculation. This is the spirit of “Share the
KANDO.”
*This is the corporate message of ASAHI BREWERIES, LTD.
It means: Always creating new value moves people’s hearts
and forms a strong bond. Always imagining a fresh
tomorrow moves people’s hearts and helps them shine.
Sharing these emotional experiences with as many people
as possible—this is the mission of the Asahi Breweries
Group.
51
reports and testimonials come from these industries. The
specialists in the design and development divisions are
becoming more and more familiar with CAE. The various
technologies are not too difficult to apply, even for beginners,
as they usually have previous experience, and the manuals and
guidelines are pretty clear. Still, CAE with stress simulation has
not been used in the pharmaceutical and food industries
worldwide until recently. Mr. Sato indeed has made a big step
forward with his idea of using CAE for tablet design. The key
success factor was the new approach of using the substituted
condition for the target simulation in cases where the real
physical condition cannot be determined. In 2010, these series
of simulations were presented at different academic meetings
and in various publications. Mr. Sato’s work and approach
received a great response from the pharmaceutical and food
industries and the CAE sector.
This article is based on the original case study by Mr. Hideaki
Sato, Research Laboratories For Food Technology, ASAHI
BREWERIES, LTD. and Mr. Takahiro Miura, Mechanical CAE Division,
CYBERNET SYSTEMS CO.,LTD.
Akiko Kondoh
Consultant for EnginSoft in Japan
Comments from Mr. Miura of CYBERNET SYSTEMS
Co.,Ltd.
CYBERNET SYSTEMS is a Japanese company offering
computational engineering solutions, such as CAE
software tools and all product-supporting services
including seminars, support and consulting. ANSYS is one
of our major business areas. We have a strong customer
base in different industries, for example in automotive,
electrical machinery, electrical devices, energy, aerospace
and medical engineering. For the past 25 years since its
establishment, CYBERNET SYSTEMS has been passionate
about supporting MONOZUKURI in Japan as a CAE solution
provider. Now, it also has some affiliated companies in
Asia, North America and Europe, and has become a global
player.
ASAHI BREWERIES GROUP is a pioneering Japanese food
and beverage manufacturer. We are truly honored to be
able to collaborate with Mr. Sato who is promoting
cutting-edge research and development. Currently, CAE is
not used extensively in the food and beverage industries
in comparison with other industries. We believe that CAEbased engineering simulation will provide effective
solutions for achieving “time savings”, “cost reduction”,
“security assurance” and “environmental protection”,
important topics also for companies in these industries.
We will endeavor to develop other examples for the
engineers in the food and beverage industries, to
encourage them to connect with and use CAE. We will also
deepen the relations with our partners, like with Mr. Sato,
and grow their passion for MONOZUKURI with our own
passion.
Tokyo a Metropolis
March 2011 Earthquake
and Tsunami in Japan
Tokyo, the capital of Japan, is the world’s biggest mega city
according to the United Nations’ 2010 report, with a population
of 13 million and 36.6 million if we include its surrounding
urban areas. Another report by PricewaterhouseCoopers (PwC)
states that Tokyo has the highest GDP of any cities in the world.
Tokyo is also the heart of Japan with regards to politics, culture
and education. When we think of Tokyo, images of typical
cityscapes with high-rise buildings standing above busy crowds,
elaborate train and subway systems, different varieties of
academic and cultural facilities along with a rich entertainment
heritage are conjured up. On the other hand, the city has many
different aspects, such as numerous parks and green areas,
waterways and finally the sea! There are many places where one
can relax and unwind watching the changes of the seasons. From
the many faces of Tokyo, I would like to introduce my favorite
spots in this article.
This article was written before a terrible earthquake hit
parts of Japan and its people.
If you want to help, please donate to:
Italian Red Cross:
http://www.cri.it
The Japanese Red Cross Society:
http://www.jrc.or.jp/english/
British Red Cross:
http://www.redcross.org.uk/
German Red Cross:
http://www.drk.de
or to any other organization that helps Japan in the
present crisis.
Thank you
The Newsletter Editorial Team
The skyscrapers
When visiting Tokyo, many of my European friends are surprised
by the cluster of high-rise buildings in different areas and the
endless expansion of crowded residential areas spread across the
suburbs. In fact, many new buildings are constructed with
incredible rapidity every year, and the landscape changes
Shinjyuku-Gyoen Park
The nightscape of Shinjyuku
constantly. The high-rise buildings of Tokyo not only overwhelm
people at daytime, they also present amazing views after sunset.
Tokyo is known all over the world for its diversity of restaurants
and gourmet places, in particular: Japanese, Italian and French
cuisine are the people’s favorite. On the top floors of some tall
buildings such as “Tokyo Midtown” in Roppongi and the
“Marunouchi Building” near Tokyo station, we can enjoy the
great bird’s eye view with a variety of gourmet food. This is truly
a unique experience. After a busy day, a lot of people in Tokyo
feel at home watching the illuminations and the slowly blinking
lights floating into the night sky.
The green oases
Surprisingly, there are many large parks with a lot of trees in
Tokyo. In Shinjyuku, located nearby the Tokyo Metropolitan
Government offices, there is a park called Shinjyuku-Gyoen that
I often visit with my family when the weather is fine. ShinjyukuGyoen is run by the Ministry of the Environment and covers an
area of 580,000 m². This beautiful park invites visitors to enjoy
gardens of three distinct styles: the French Formal Garden, the
English Landscape Garden and the Traditional Japanese Garden.
In spring, the park’s 1300 cherry trees attract many visitors as
one of the best cherry blossom-viewing spots in Japan. A short
distance from Shinjyuku, there is another large green oasis
called Meiji-Jingu, it is the home of a famous Shinto shrine and
covers 700,000 m². Meiji-Jingu is surrounded by a very old manmade forest. As soon as you enter the area, you will feel a
sublime atmosphere, far from the hustle and bustle of the city.
Once you have passed the wooden approach, you will reach the
main hall enshrining a God, a treasure museum called
Homotsuden and Shiseikan of martial arts. At week-ends, you
might even be able to see a traditional Japanese wedding
ceremony.
Asakusa – the old town of Tokyo
Dwarfed by the modern buildings, Tokyo’s old towns welcome
visitors with warmth and old world charm. The most famous
town is Asakusa which is very popular among foreign travelers.
Senso-ji Temple
The Senso-ji temple can be found here, it is world-renowned for
its Kaminari-mon. The existing main hall and five-story pagoda
were reconstructed after having been burned down during the
Second World War. The original buildings date back to more than
a thousand years ago, and they are historical and symbolic
temples of Tokyo. Along the approach from the Kaminari-mon to
the Hozo-mon, there are many souvenir and snack shops lining
up a street called Nakamise. Here we can enjoy shopping in a
very Japanese atmosphere. The neighborhood is dotted with lots
of classic restaurants, which will satisfy your appetite with very
authentic Tokyoite dishes, such as Tenpura, Sukiyaki and Unagi.
On the west side, there is Kappabashi, a street devoted to
kitchenware, which supplies most of the restaurants in Tokyo.
Recently, so-called ultra-realistic food models are sold here
which have become very popular as souvenirs.
Returning to the east side of the Senso-ji temple, there is the
Sumida river, where you can enjoy a nice walk and maybe a short
trip on a cruise boat. Behind the red painted Azuma-bashi
bridge, the headquarters of ASAHI BREWERIES, LTD. are located,
the Japanese Group that we introduce in this Newsletter with
the CAE tablet design case study. It is a major landmark because
of the golden flame on top of the black building. On the left of
the ASAHI BREWERIES buildings, the world’s tallest TV tower
“Tokyo Sky Tree” appears. It is still under construction. In
February 2011, its height has reached 574m. The construction
will be completed at the end of 2011, the final height will be
634m. The number 634 was selected because of its
pronunciation in Japanese which is MUSASHI, the old name of
the Tokyo metropolitan area.
53
ODAIBA the bay area
Odaiba is the bay area which did not exist in the old maps
because it was constructed by massive landfills towards the end
of the last century, and the current landscape only appeared
after the 1990’s. Towards the end of the Edo Period (16031868), a number of forts were built here on the different islands
in the bay, to protect Tokyo against possible attacks from the
sea. More than a century later, Tokyo began a spectacular
development project aimed to relieve the congestion in the city
center, and it became a large business and residential district
starting with the opening of the Rainbow Bridge. The beautiful
scenery of neo-futuristic streets and the bay area, attracts many
visitors from all parts of the country to Odaiba.
Odaiba is, at the same time, a favorite place for engineers. Many
trade shows dedicated to the manufacturing and CAD/CAE
industries are held at this “Tokyo Big Sight” which was opened
in 1996. The hotels in this area are often chosen as venues for
different Users’ Meetings of CAD/CAE software products.
Rainbow Bridge in Odaiba
Savor the Cuisine of Tokyo
One of the major attractions of Tokyo is its cuisine and unique
gastronomic variety. Here, locals and visitors from all parts of
Japan and around the world, savor different kinds of Japanese
food and the cuisines from many other cultures. In Tokyo, we
can enjoy food of the highest qualities and standards at
reasonable prices.
If you visit Tokyo and wish to look for a suitable restaurant,
there are several handy search guides you can use, for example
GourNavi. You can select from a wealth of information based on
location, food type and price range.
If you search e.g., for a restaurant near Roppongi, about 2,000
restaurants will come up very quickly (100 on the English
website). In case you are tired at some stage, from all the going
out to restaurants, why not discover DepaChika, the department
store's basement food floor in the station. Here you can buy your
favorite dishes from a variety of choices and take them to a
nearby park or wherever you are staying – this is very easy and
convenient and what the locals do also!
Tokyo is one of the biggest and most modern metropolis in the
world. At the same time, it is also a very interesting city that
has always maintained its originality, a melting-pot of nature,
people’s love for nature and traditional cultures…
There is so much more about Tokyo that we will bring to you in
the next Japan Columns of the Newsletter!
The headquarters of ASAHI BREWERIES, LTD., and Tokyo Sky Tree
Akiko Kondoh, Consultant for EnginSoft in Japan
President Obama Honors EnginSoft’s
Partner with the Presidential Early
Career Award for Scientists and
Engineers
Prof. Gianluca Iaccarino has been
recognized last December with the
Presidential Early Career Award for
Scientists and Engineers (PECASE), the
highest honor the U.S. government
bestows on scientists and engineers in
the early stages of their research careers,
during an official ceremony at the White
House in Washington D.C. Prof.
Iaccarino, one of 13 U.S. Department of
Energy researchers named as recipients,
was recognized for “his extensive and
deep scientific contributions in the areas
of turbulent flow and uncertainty
quantifications for the National Nuclear
Security Administration community,”
according to a Department of Energy
official. The award winners were honored
for their research efforts in a variety of
fields, from helping the nation achieve
energy independence to exploring the realms of space to
identify dark matter. These awardees are funded by the U.S.
Department of Energy's Office of Science and the National
Nuclear Security Administration. The winning DOE scientists
are among 85 researchers supported by 10 federal
departments and agencies who have received the award. In
addition to a citation and a plaque, each PECASE winner will
continue to receive DOE funding for up to five years to
advance his or her research.
“Science and technology have long been at the core of
America's economic strength and global leadership I am
confident that these individuals, who have shown such
tremendous promise so early in their careers, will go on to
make breakthroughs and discoveries that will continue to move
our nation forward in the years ahead” said President Obama.
“These gifted young scientists and engineers represent the best
in our country. The awards recognize ingenuity, dedication,
diligence and talent. I congratulate the PECASE awardees and
wish them continued success towards new discoveries and
advances in science, energy research, and national security”
said Secretary Steven Chu.
The Award Motivation
“For his extensive and deep scientific contributions in the
areas of turbulent flow and uncertainty quantifications and
quantified margins of uncertainty, which are
amplified for the National Nuclear Security
Administration (NNSA) community through
his position of intellectual leadership at the
NNSA Predictive Science Academic Alliance
Program Center at Stanford”
Nominated by Lawrence Livermore National
Laboratory
Prof. Gianluca Iaccarino
Dr. Gianluca Iaccarino is an Assistant
Professor at Stanford University with joint
appointments in the Mechanical Engineering
Department and the Institute for
Computational Mathematical Engineering. He
completed his graduate studies in Italy
working on computational methods for fluid
dynamics and worked as a Research
Associate at the NASA Center for Turbulence
Research before joining the Faculty at
Stanford in 2007. He is the Deputy Director of the NNSA
Predictive Science Academic Alliance Program (PSAAP) Center
at Stanford and leads the effort on Quantification of Margins
and Uncertainties, a decision-making computational
framework aimed at managing risks associated to highconsequence systems. His research activities are focused on
Computational Fluid Dynamics, in areas ranging from analysis
of wind turbines, to hypersonic propulsion, to turbulence and
transition modeling, to thermal management in batteries. In
2007 Dr. Iaccarino funded the Uncertainty Quantification Lab
(http://uq.stanford.edu): a joint initiative between the
School of Engineering and the Mathematics and Statistics
Departments. The UQLab is supported by various grants from
NNSA, DOE Office of Science, NSF, and industries and focuses
on probabilistic algorithms
for uncertainty analysis,
stochastic inference and
robust optimization. The
research work ranges from
the theoretical aspects of
uncertainty representation,
to algorithms for nondeterministic analysis, to
large-scale
applications
leveraging massively parallel
computers. Many of the
current projects involve
active collaborations with Sandia,
Lawrence Livermore and Los Alamos
National Laboratories. Dr. Iaccarino is
involved in various educational
activities at Stanford and in the
computational engineering community.
He
organized
Uncertainty
Quantification tutorials, workshops and
special sessions at major engineering
conferences. He has published more
than 50 papers in both engineering
and mathematics journals and about 70
conference papers. He is also a
Humboldt fellow at the University of
Munich, Germany.
Dr. Iaccarino is also the Director of the
Thermal and Fluid Sciences Affiliates
and Sponsors Program (TFSA http://www.stanford.edu/group/tfsa/) which EnginSoft has
recently joined and he is also one of the co-founders of
Cascade
Technologies
Inc.
(http://www.cascadetechnologies.com), EnginSoft’s Partner
Company in Palo Alto (California) that develops, markets, and
supports state of the art Computational Fluid Dynamics (CFD)
analysis tools for engineering applications across industries.
About the Award
The Presidential Early Career Award for Scientists and
Engineers (PECASE) is the highest honor bestowed by the
United States government on outstanding scientists and
engineers in the early stages of their independent research
careers. The White House, following recommendations from
participating agencies, confers the awards annually. To be
eligible for a Presidential Award, an individual must be a U.S.
55
citizen, national or permanent resident.
Winning scientists and engineers receive up
to a five-year research grant.
History
In February 1996, the National Science and
Technology
Council
(NSTC),
was
commissioned by President Bill Clinton to
create an award program that would honor
and support the achievements of young
professionals at the outset of their
independent research careers in the fields of
science and technology. The stated aim of
the award is to help maintain the leadership
position of the United States in science.
Originally, 60 recipients received the PECASE
award per year. Due to increased
participation by the Department of Defense,
this has increase to 100 per year. The 2002 PECASE awards
were not announced until May 2004 due to bureaucratic
delays within the Bush administration.
Agencies
The agencies participating in the PECASE Awards program
are: Department of Agriculture, Department of Commerce,
Department of Defense, Department of Energy, Department of
Education, Department of Health and Human Services:
National Institutes of Health, Department of Veterans Affairs,
National Aeronautics and Space Administration, and the
National Science Foundation.
From Wikipedia, the free encyclopedia:
http://en.wikipedia.org/wiki/PECASE
Formazione a distanza sugli
elementi finiti
EnginSoft ha messo a punto e sostiene, per conto di Consorzio
TCN, l'iniziativa di formazione a distanza in ingegneria “improve.it”, con l’obiettivo di creare una risorsa di alta formazione
continua, coerente con gli obiettivi di formazione del Consorzio.
Tramite il portale all’indirizzo http://www.improve.it è possibile
accedere a corsi multimediali di auto-formazione sui temi della
simulazione numerica e prototipazione virtuale e temi a questi
complementari e affini.
Nel 2010 il portale improve.it è stato completamente rinnovato
sia nella grafica che nei contenuti. Tra le nuove funzionalità offerte da improve.it sono disponibili il nuovo sistema di ricerca
dei contenuti e la nuova procedura online per l’acquisto dei corsi. Il contenuto di tutti i corsi disponibili è inoltre stato migliorato e per la loro erogazione viene ora utilizzato un nuovo sistema multimediale di elevata qualità.
Istantanea di una delle lezioni multimediali che compongono il corso
zioni di forma, convergenza della soluzione, utilizzo di elementi di ordine superiore al primo.
Il catalogo dei corsi è costantemente aggiornato e riportato sul
sito. Per ogni corso è disponibile il programma dettagliato. È
inoltre consentito l'accesso gratuito ad alcuni corsi. Sono oggi
disponibili on-line corsi a vari livelli relativi a metodo degli elementi finiti, analisi statica e dinamica, fluidodinamica computazionale, acustica computazionale, elettromagnetismo, progettazione, ottimizzazione multi-obiettivo, scienza dei materiali, processi produttivi, metallurgia…
Nuovo corso online 2011 di introduzione al FEM
Il metodo degli elementi finiti: teoria e applicazioni meccanico-strutturali in campo elastico lineare
Docente del corso: Prof. Leonardo Bertini, Dipartimento di
Ingegneria Meccanica, Nucleare e della Produzione, Università di
Pisa. Il corso, suddiviso in tre unità didattiche per un totale di
19 moduli multimediali, si propone di fornire gli strumenti teorici e applicativi per l'impiego corretto e ragionato del metodo
degli elementi finiti per lo studio di strutture meccaniche in
campo elastico lineare.
Prima unità didattica:
le basi teoriche del metodo degli elementi finiti
Vengono sviluppati otto moduli per introdurre la teoria del metodo degli elementi finiti, in modo semplificato e attraverso
l'utilizzo di numerosi grafici ed esempi. Gli argomenti trattati includono: discretizzazione, campo di spostamenti, calcolo delle
deformazioni, analisi agli elementi finiti, vincoli e carichi, fun-
Seconda unità didattica: applicazioni del metodo FEM alle principali classi di problemi strutturali in campo elastico lineare
Nei successivi dieci moduli del corso vengono passate in rassegna le principali famiglie di elementi finiti e per ciascuna di esse vengono forniti esempi di applicazione e limiti di utilizzo. In
particolare vengono affrontati i seguenti tipi di elemento: asta,
trave, pipe, piani, di Fourier, gap, guscio assialsimmetrico, elementi guscio/piastra 3D, brick.
Terza unità didattica: analisi critica dei risultati di un modello
FEM e criteri generali di modellazione con il metodo degli elementi finiti
I due moduli conclusivi del corso affrontano i criteri generali di
modellazione FEM e introducono l'analisi critica dei risultati attraverso esempi sui seguenti argomenti: singolarità dello stato
di tensione, definizione e schematizzazione dei vincoli, utilizzo
delle simmetrie.
Materiali aggiuntivi e questionario di autovalutazione
Oltre al materiale multimediale della durata complessiva di 4
ore, il corso offre tracce di esercizi da svolgere tramite analisi
agli elementi finiti, e un questionario di autovalutazione della
comprensione degli argomenti trattati, composto da 20 domande a risposta multipla. Agli iscritti che affronteranno positivamente il questionario di vautazione verrà inviato l'attestato di
partecipazione al corso. All'interno del corso è disponibile il forum privato per porre domande al docente. Agli iscritti al corso,
oltre all'accesso ai materiali didattici, verranno inviate le dispense a colori con la riproduzione delle oltre 280 diapositive
utilizzate dal Docente nelle lezioni.
Per informazioni e iscrizioni:
http://www.improve.it
57
REACTIVE BUSINESS INTELLIGENCE
From Data to Models to Insight
usually dissected in books
dedicated to different areas.
Brevity and attention to the
essential ideas and methods
were our design principles.
The new book by Roberto Battiti and Mauro Brunato is
now available:
ROBERTO BATTITI AND MAURO BRUNATO.
Reactive Business Intelligence.
From Data to Models to Insight.
Reactive Search Srl, Italy, February 2011.
ISBN: 978-88-905795-0-9
Readers of the EnginSoft
Newsletter
deal
with
engineering
simulations,
models and designs and do
not need many words to
understand the powerful
combination of models, simulators, and interactive
visualizations.
We hope that this book will be useful to researchers and
practitioners in widely different areas and business
sectors.
Take the plunge into
Reactive Business Intelligence!
Reactive Business Intelligence is much more than “pretty
pictures”. It is about integrating data mining, modeling
and interactive visualization, into an end-to-end
discovery and continuous innovation process powered by
human and automated learning.
The concept is illustrated in the figure RBI: reactive
business intelligence. This holistic and unifying goal
requires collecting and integrating topics which are
The School of Athens, by the Renaissance artist Raphael, 1510.
Last but not least, using proper visualizations can provide
us with aesthetic satisfaction and even artistic emotions,
although maybe not to the same extent as Raffaello’s “The
School of Athens”…
To buy this book, please visit the book’s web page:
http://reactivebusinessintelligence.com/
By inserting the coupon code ENGINSOFT-RBI, a special
20% discount will be applied (this offer ends on 31st May
2011).
EnginSoft at the Optimization Day:
Research and Applications
EnginSoft joins the Thermal and Fluid Sciences Affiliate
Program of Stanford University and Sponsors a One Day
Seminar on Optimization.
EnginSoft has recently strengthened its North American
operations by means of expanding both the
office’s space and the employed personnel at its
Silicon Valley office, located at the Palo Alto
Technology Center (San Francisco Bay Area California).
With the aim of stimulating the networking in
the area as well as of providing continuous
support and commitment to scientific research,
EnginSoft has also joined the TFSA (Thermal and
Fluid Sciences Affiliate) of Stanford University
and has been welcomed as a new member
during the 2011 TFSA conference which took
place at the Munger Conference Center, inside
the Stanford University Campus, in Palo Alto on
February 2-4, 2011.
The conference is organized every year within
the TFSA program and is aimed at presenting
the latest research work of the Stanford Thermal
and Fluid Sciences program. This year’s
conference has been enriched and anticipated
by a One-Day Seminar on Optimization (the
“Optimization Day”) which has been held on
February 1st, at Stanford Campus. The event, as
part of TFSA program, has been organized by
Prof. Gianluca Iaccarino and EnginSoft ’s staff
in Palo Alto. EnginSoft has indeed sponsored
and fully supported the event with the intent of
stimulating the discussion on optimization as
an effective and practical means for
engineering practice, while bringing its
contribution in terms of leading technology
(modeFRONTIER) and expertise in the field of MultiObjective Design Optimization, in particular with respect
to Computational Fluid Dynamics (CFD) applications. The
many applications of optimization that were presented
59
including affiliates representatives, sponsors of
research, and special guests, and the technical program
was made up of more than 50 oral presentations and a
poster session. Several topics were covered with
contributions in various areas of our research activities,
including predictive science, aeroacustics and noise,
fluid mechanics, LES, combustion (modeling and
diagnostic) heat transfer, energy science, processing
and engineering of materials, micro-scale flow and heat
transfer and fuel cells, as well as issues regarding design
Optimization under design uncertainties. Several new
initiatives that are providing substantial growth in the
research activities and new opportunities for industrial
collaboration were described. During the last day of the
conference, a lab tour was organized so as to illustrate the
capabilities and state of the art of the Stanford labs and
computing facilities. Finally, a dinner banquet at the
Stanford Faculty Club was held; it was there that the best
presentations and scientific papers were awarded
(http://www.stanford.edu/group/tfsa/).
ranged from Rapid Product Development to Web searching,
from Sophisticated Multidisciplinary Analysis to Robust
Design Under Uncertainty. In each specific presentation
the following questions were addressed: What are the
Remaining Barriers for Optimization Algorithms? How are
Present Computational Resources Changing the Paradigm
of Engineering Design? Are Current Optimization Methods
Sufficient to Drive Decision-Making? The objective of
bringing together Stanford faculty and industrial
representatives to discuss the
current applications and
Examples from Some Papers
remaining bottlenecks to the
adoption of Optimization TFSA Conference 2011
Algorithm
was
achieved
“Large-Eddy Simulation of Active Flow Control”, by
through this event with a
Parviz Moin (Stanford Univ.) and Arvin Shmilovich
great success of attendance.
(Boeing)
Companies like Rolls Royce
and GE illustrated their
activities on aeroengines,
while Ferrari brought its
experience from its Formula 1
racing activities. Stanford
faculty members illustrated
their wide experience in
aerodynamic
design
via
control theory (Prof. A.
Jameson) and gave talks on
frontier topics such as optimal
design under uncertainties
(Prof. G. Iaccarino).
The following 3 days (2-4
February) the TFSA convened
for its annual conference,
covering advanced topics in
CFD introduced by Professor
Parviz Moin. The conference is
the main event organized
within the program every year
in February. It was an exciting
conference presenting the
latest work of the Stanford
Thermal and Fluid Sciences
program. The 2011 conference
had over 100 participants,
Presented at the
LES of Supersonic Jets from Complex Nozzles“ by
Joseph W. Nichols, Frank E. Ham, Yaser Khalighi,
Sanjiva K. Lele, and Parviz Moin
NAFEMS World Congress 2011 Preliminary Agenda Announced
International Association for the
Engineering
Analysis
Community
Releases Line-up for Global Simulation
& Analysis Conference
GLASGOW, UK, FEBRUARY 18TH 2011 –
NAFEMS, the International Association for
the Engineering Analysis Community, has
announced the preliminary agenda for its
2011 World Congress, being held in
Boston, MA, USA between May 23rd and
26th. Including over 150 presentations in more than 40
sessions over three days, this represents the most
comprehensive and wide-ranging collection of analysis and
simulation specific papers available from one independent,
international event.
Keynote speakers at the Congress will include;
• Marc Halpern: Gartner, Inc., USA
• Mike Hinton: QinetiQ, United Kingdom
• Alexander Karl: Rolls-Royce Corporation, USA
• Ronald Krüger: National Institute of Aerospace, USA
• Wiley Larson: Stevens Institute of Technology, USA
• Laura Michalske: Procter & Gamble, USA
The full agenda is available to view, and to download, from
the Congress website at www.nafems.org/congress.
Registration is also available here, as well as full details of
the location, venue and exhibition opportunities.
About NAFEMS
NAFEMS is a not for profit organization aimed at
promoting best practices and fostering education and
awareness in the engineering analysis community. In line
with its objectives to promote the effective use of
simulation technologies, NAFEMS is continually seeking
to create awareness of new analysis methodologies,
deliver education & training, and stimulate the adoption
of best practices and standards by offering a platform for
continuous professional development. For more
information, visit www.nafems.org.
Further information and high-resolution images are
available on request.
Tim Morris from NAFEMS is available for further comment
by arrangement.
A number of short training courses and special workshops will
also be available for delegates to attend, ensuring that their
time in Boston is used to maximum effect.
As many as 6 parallel tracks will run over the three days of
the Congress, covering topics including;
• Optimization
• Integration
• Composites
• Materials
• CFD
• Fatigue & Fracture
• Geotechnics
• MBS
• Industrial Applications
• Business Benefits
• Dynamics & Testing
• Education
• Analysis Management
• Simulation Data Management
• Seismic Analysis
• High Performance Computing
• Business Benefits of Simulation
• …and many more
The NAFEMS World Congress is the only event dedicated to
showcasing the state-of-the-art and state-of-practice in the
simulation world in an impartial forum, open to everyone
with an interest in how to get the most from their use of
simulation.
Visit
the
Congress
website
at
http://www.nafems.org/congress to find out more, and to
register for the only independent, international conference
dedicated to analysis and simulation technology.
Press Contact
David Quinn (NAFEMS),
+44 (0) 13 55 22 56 88 [email protected]
61
EnginSoft alla Fiera
Made in Steel di Brescia
Dal 23 al 25 marzo 2011 si è svolta presso il centro fiera
Brixia Expo Fiera di Brescia la quarta edizione di Made in
Steel, un evento biennale dedicato alla filiera dell’acciaio.
Made in Steel 2011 ha registrato un record di visite rispetto
alle sue precedenti edizioni: 13.500 visitatori, provenienti da
46 nazioni, confrontati con i 12.000 della scorsa edizione nel
2009. Un aumento rilevante anche nel numero degli espositori, salito da 187 a 248, e di conseguenza nell’area espositiva (da 7.400 a 10.200 mq). Va ricordata inoltre la presenza
delle delegazioni estere di Austria, Bielorussia e Cina.
EnginSoft ha partecipato a Made in Steel con uno stand, focalizzando l’attenzione sui software e le applicazioni specifiche
per il settore metallurgico, in particolare quelle sostenute da:
MAGMA (MAGMAsteel e MAGMAfrontier), Transvalor (FORGE) e
Third Wave Systems (AdvantEdge FEM e Production).
La fiera è stata visitata prevalentemente da manager e il nostro stand ha registrato un buon afflusso di persone appartenenti ad importanti aziende con le quali sono stati organizzati degli incontri riservati dove sono stati discussi problemi
specifici e ipotesi per future collaborazioni.
Il terzo giorno, venerdì 25 marzo, la nostra società ha organizzato presso la Sala Steel il seminario dal titolo: “Energia
Nucleare di nuova generazione: engineering e design di processo e di prodotto”. I relatori sono stati Piero Parona, che
ha illustrato la mission di EnginSoft e le proprie referenze,
Marcello Gabrielli le applicazioni di FORGE dedicate ai forgiatori d’acciaio, Enrico Borsetto quelle di ADVANTEDGE per le
lavorazioni meccaniche, Gianluca Quaglia quelle di MAGMA
dedicate ai processi di fonderia e di Trattamento Termico e
Massimo Galbiati quelle FEM di tipo fluidodinamico, termico
e strutturale. Erano presenti una cinquantina di partecipanti
provenienti da importanti aziende fra le quali ThyssenKrupp,
il Gruppo Cividale, il Gruppo FOMAS e Hydromec, importante
costruttore di presse bresciano col quale EnginSoft ha siglato un accordo di collaborazione tecnologica che porterà
Hydromec ad utilizzare FORGE per studiare nuove soluzioni di
stampaggio e alla proposta congiunta di seminari tecnici per
specifici settori dello stampaggio.
Nel complesso Made in Steel è stata un’esperienza positiva
che ha dato modo ad EnginSoft di farsi conoscere maggiormente nel settore metallurgico, dove è presente da circa dieci anni con clienti molto importanti, ma che può essere ulteriormente sviluppato.
Hydromec srl ed Enginsoft hanno siglato
un accordo di collaborazione tecnologica.
Brescia 1 Marzo 2011 – Hydromec srl, azienda di riferimento
nella progettazione e costruzione di presse per lo
stampaggio dei metalli ed Enginsoft, società italiana di
maggior consistenza e tradizione nel settore della
sperimentazione virtuale e del CAE, hanno siglato un accordo
di collaborazione tecnica finalizzato all'integrazione e
sviluppo delle proprie tecnologie.
Il processo di stampaggio dei metalli rappresenta oggi un
settore manifatturiero di grande importanza e ad alto
contenuto di sviluppo potenziale e, per questo motivo, le
due Società hanno deciso di condividere know-how ed
esperienze.
Da una parte la tecnologia meccanica, la qualità dei
materiali e l'accuratezza di progettazione con sistemi
innovativi di controllo e gestione di Hydromec srl, dall'altra
software di simulazione, come Forge e Ansys, e di
ottimizzazione dei parametri di processo come
modeFRONTIER, rappresenteranno una base innovativa per
risolvere le problematiche e le applicazioni tecnologicamente
sempre più complesse che i processi di stampaggio oggi
richiedono.
Hydromec srl
Fondata nel 1980, Hydromec srl nasce
come azienda per la revisione di
macchine.
Ben presto Hydromec srl dirige i propri sforzi produttivi verso
il settore dello stampaggio a caldo dell'ottone. Nascono così
le presse della serie HF che si avvalgono di ben dieci brevetti
tecnici. Successivamente Hydromec srl amplia la propria
gamma di prodotti realizzando le presse oleodinamiche a
quattro colonne della serie HSF utilizzate nel settore della
forgiatura dell'acciaio a caldo, cui si aggiungono i laminatoi
della serie LAR per la produzione di anelli, flange e sagomati
in acciaio. Il Sistema Gestione Qualità di Hydromec è
conforme alle norme UNI-EN ISO 9001:2008.
Per informazioni e contatti: www.hydromec.it
EnginSoft Event Calendar
ITALY
EnginSoft is pleased to announce the next Seminars and
Webinars. For more information, please contact:
[email protected]
Please visit www.enginsoft.com
EnginSoft International Conference 2010
CAE Technologies for Industry.
To receive a copy of the The Conference Proceedings, please
contact: [email protected]
EnginSoft International Conference 2011
CAE Technologies for Industry
Fiera di Verona - ITALY • 20-21 October 2011
Please stay tuned to www.caeconference.com for one of the
major events for CAE Users in Europe!
FRANCE
EnginSoft France 2011 Journées porte ouverte
dans nos locaux à Paris et dans d’autres villes de France, en
collaboration avec nos partenaires.
Pour plus d'information visitez: www.enginsoft-fr.com,
contactez: [email protected]
Webinars Flowmaster: Introduction au logiciel Flowmaster
• 31 March
• 14 April
18 May - Etats Généraux Micado. France
http://www.enginsoft-fr.com/events/index.html
15-16 June - Séminaire modeFRONTIER au CETIM
Cetim Senlis.
20-26 June - Salon du Le Bourget - Paris Air Show
Le Bourget, Paris.
Talk to our experts at the EnginSoft/ Flowmaster booth!
http://www.paris-air-show.com/en
18-29 June – Teratec Conference. Ecole Polytechnique
Palaiseau. Meet us at the EnginSoft / Flowmaster booth!
12 October - User Group Meeting modeFRONTIER France. Paris
13 October - User Group Meeting Flowmaster France. Paris
GERMANY
Please stay tuned to: www.enginsoft-de.com
Contact: [email protected] for more information.
modeFRONTIER Seminars 2011. EnginSoft GmbH, Frankfurt
am Main. Attend our regular Webinars and Seminars
to learn more on how design optimization with
modeFRONTIER.
can enhance your product development processes
14-15 April - Efficient Design of Composite Structures –
ESAComp Users' Meeting 2011. Technical University of
Munich, Institute for Carbon Composites
EnginSoft will be presenting: Optimization and robustness of
composite structures: The whole design chain driven by
modeFRONTIER
In addition to presentations on simulation and design of
composite structures, the latest advances in the ESAComp
software will be presented. Three workshops will be held: the aerospace industry, - wind, marine energy and industrial
applications, - optimizing composite structures.
EnginSoft is a sponsor of the Users’ Meeting
http://www.enginsoft.com/events/esacomp_um.pdf
www.esacomp.com
Seminars Process Product Integration
EnginSoft GmbH, Frankfurt am Main
How to innovate and improve your production processes!
Seminars hosted by EnginSoft Germany and EnginSoft Italy
SPAIN
Programa de cursos de modeFRONTIER and other local events
Please contact our partner, APERIO Tecnología:
[email protected]
Stay tuned to: www.aperiotec.es
10 March - National Instruments Day - Barcelona. Discover
the latest trends in technology and new products from
National Instruments during the Technology Forum on
Graphic Design Systems.
AperioTec and ESTECO will be present to show the latest dedicated connection between modeFRONTIER and NI LabView.
Participation is free. http://www.ni.com/nidays/es/
5-8 June - IDDRG 2011 International Conference. Bilbao (País
Vasco). This year, in addition to stamping, material characterization, numerical simulation and tooling normally covered, the organizers would like to focus the conference on su-
stainability: of global concern, not only for industry but also
for consumers, politicians and business leaders.
For more information, please visit:
http://www.iddrg2011.eu/
SWEDEN
2011 Training Courses on modeFRONTIER - Drive your designs
from good to GREAT EnginSoft Nordic offices in Lund, Sweden
The Training Courses are focused on optimization, both multi- and single-objective, process automation and interpretation of results. Participants will learn different optimization
strategies in order to complete a project within a specified
time and simulation budget.
Other topics, such as design of experiments, metamodeling
and robust design are introduced as well. The two day training consists of a mix of theoretical sessions and workshops.
• 7-8 April
• 2-3 May
• 7-8 June
• 11-12 August
• 5-6 September
• 4-5 October
• 2-3 November
• 1-2 December
To discuss your needs, for more information and to register,
please contact EnginSoft Nordic, [email protected]
UK
The workshops are designed to give delegates a good appreciation of the functionality, application and benefits of
modeFRONTIER. The workshops include an informal blend of
presentation plus ‘hands-on’ examples with the objective of
enabling delegates to be confident to evaluate
modeFRONTIER for their applications using a trial license at
no cost.
modeFRONTIER Workshops
Warwick Digital Laboratory, Warwick University
• 12 April
• 12 May
• 21 June
• 20 July
• 17 August
• 14 September
• 13 October
• 22 November
• 14 December
• 16-17 May
• 6-7 September
For more information and to register, please visit www.enginsoft-uk.com. Contact: Bipin Patel, [email protected]
24-25 May - National Manufacturing Debate 2011. Vincent
Building (Building 52), Cranfield campus, Cranfield
University EnginSoft will be attending.
www.cranfield.ac.uk/sas/manufacturingdebate
27-29 April - ESAFORM 2011. 14th International ESAFORM
Conference on Material Forming. Belfast, Northern
Ireland/UK. The purpose of this conference is to facilitate
the communication between specialists in various fields of
material forming sciences. Presentations concerning all the
steps of material forming processes are welcome: from fundamental studies to applied aspects, from experimental to numerical research. Gino Duffett of AperioTec has been invited
to give a plenary on advances and the future of simulation in
the manufacturing industry
www.qub.ac.uk/sites/ESAFORM2011/
GREECE
9 May - 5th PhilonNet CAE Conference. Athens. If you would
like to present your work with ANSYS (including CFX, Fluent
and Ansoft products), ANYBODY, DIFFPACK, ESACOMP, eta/DYNAFORM,
eta/VPG,
Flowmaster,
FTI,
LS-DYNA,
modeFRONTIER, MOLDFLOW, SIMPLEWARE or ADVANTEDGE
please send your abstract to: [email protected]
For more information, please visit: www.philonnet.gr
USA
Courses on Design Optimization with modeFRONTIER
Sunnyvale, CA
For more information, please contact: [email protected]
www.ozeninc.com
JAPAN
17 June - CDAJ CAE Solution Conference 2011
modeFRONTIER Conference Day
PAN PACIFIC Yokohama Bay Hotel Tokyu
http://www.cdaj.co.jp/
modeFRONTIER Workshops with InfoWorks CS Warwick Digital
Laboratory
• 26 May
• 9 November
Please register for free on www.enginsoft-uk.com
Multi-Disciplinary
Optimization
Training
International Digital Lab, Warwick University
63
Course.
Europe, various locations
modeFRONTIER Academic Training
Please note: These Courses are for Academic users only. The
Courses provide Academic Specialists with the fastest route
to being fully proficient and productive in the use of
modeFRONTIER for their research activities. The courses combine modeFRONTIER Fundamentals and Advanced
Optimization Techniques.
For more information, please contact Rita Podzuna,
[email protected]
To meet with EnginSoft at any of the above events, please
contact us: [email protected]
www.caeconference.com
®
ANSYS ITALIAN
CONFERENCE 2011
Two major events coming together for the most significant occasion in the Italian CAE Calendar
APERS
CALL FOR P
EN
IS NOW OP
CAE TECHNOLOGIES FOR INDUSTRY
ENGINSOFT INTERNATIONAL
CONFERENCE 2011
VERONA -IT 20-21 OCTOBER

ICEPAK 13.0: buone notizie per i progettisti elettronici

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