# Simulation of a Launch and Recovery of an UUV to an

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Simulation of a Launch and Recovery of an UUV to an

2009 Master’s Thesis in Naval Architecture Simulation of a Launch and Recovery of an UUV to an Submarine Robert Fedor KTH Marina System 2009-10-21 Acknowledgments I wish to extend the outermost thanks to ASC Pty Ltd and Hans Wicklander for giving me the opportunity to conduct this study at location in Adelaide, Australia. Also thanks to Patrick Marshallsay, Sean Williams and Per Dahlander who guided me with their expertise in the field. Christine Philippou without you I would have been lost in the office. Richard Hejde, Roger Carlsson, Anders Folbert and Paul Plant for your input and friendship. Jens Fellenius and Lynda Curtis for your hospitality, friendship and above all help with my living arrangements. Marucs Leach and Brant Oxlade for teaching me how to surf. My family for their support throughout my studies with a special thought to my late father Henry Fedor, who tragically passed away during the course of this study, may you rest in peace. 2 Abstract Studies of the flow field surrounding submarines are a common practise, usually to be able to lower the underwater signature of the vessel. In this report the study has focused on mapping the forces the flow field and boundary layer exerts on an adjacent, much smaller, vehicle trying to dock with the submarine. From requirements defined by ASC Pty Ltd the recovery procedure have to be conducted while at speed. The submarine was modelled and simulated in a CFD tool with the Unmanned Underwater Vehicle at different locations along the hull of submarine. The simulation showed that the boundary layer and vortices surrounding the submarine are highly complex. With the CFD code and present computing power available at the time of this report it was impossible to accurate map the flow. However it is shown that the forces fluctuate almost chaotically and with current manoeuvrability technology and recovery systems for Unmanned Underwater Vehicles it is highly unlikely that a safe docking could be conducted at speed. 3 Sammanfattning Studier av vattnets flöde kring ubåtar är vanligt förekommande, vanligtvis för att minska den akustiska signaturen hos farkosten. Denna studie fokuserar på att försöka kartlägga den turbulens och de krafter som uppkommer i gränsskiktet och flödet kring en ubåt när en mindre farkost försöker docka till den. Enligt kravspecifikationen definierad av ASC Pty Ltd så måste den tänkta dockningen ske i fart. Ubåten har modellerats och simuleras i ett CFD-verktyg tillsammans med en obemannad undervattensrobot placerad på olika platser utmed ubåtens skrov. Resultatet från simuleringarna visade att gränsskiktet och turbulensen kring ubåten är mycket komplext. Med den CFD kod och datorkraft som fanns tillgänglig för författaren vid tillfället för studien var det omöjligt att kartlägga flödet i detalj. Det visar sig dock att krafterna har en näst intill kaotisk fluktuation och i relation med dagens manövreringsförmåga hos obemannade undervattensfarkoster samt de dockningssystem som finns tillgängliga är det högst osannolikt att en säker dockning skulle kunna utföras i fart. 4 Table of contents 1 INTRODUCTION......................................................................................................................... 9 1.1 SCOPE ......................................................................................................................................... 9 1.1.1 Limitations ........................................................................................................................ 9 2 APPROACH TO THE FLUID DYNAMIC PROBLEM......................................................... 11 2.1 THE MODEL .............................................................................................................................. 11 2.2 THE DARPA SUBOFF PROJECT .............................................................................................. 12 2.2.1 Axisymmetric Hull .......................................................................................................... 12 2.2.2 Sail.................................................................................................................................. 12 2.3 GOVERNING EQUATIONS ........................................................................................................... 12 2.4 FLOW AROUND A SUBMARINE ................................................................................................... 13 2.4.1 Boundary layer ............................................................................................................... 13 2.4.2 Tip and Junction flows at the sail ................................................................................... 13 2.5 CHOICE OF POSITIONS ............................................................................................................... 14 3 CFD AND THE STAR-CCM+ CODE ...................................................................................... 17 3.1 STAR CCM+ (THE CODE) .......................................................................................................... 17 3.1.1 The mesh ......................................................................................................................... 17 3.1.2 AMG SIMPLE Solver...................................................................................................... 19 3.2 REYNOLDS-AVERAGED NAVIER-STOKES (RANS).................................................................... 20 3.3 TURBULENCE MODELS.............................................................................................................. 21 3.4 DETACHED EDDY SIMULATION (DES)...................................................................................... 22 3.5 UNCERTAINTY ANALYSIS OF THE PROBLEM AND CODE ............................................................. 22 3.5.1 Scaling of CFD model .................................................................................................... 24 3.5.2 Presentation and reduction of Data................................................................................ 26 3.5.3 Grid size and dependence study...................................................................................... 27 3.5.4 Deciding the Time-step for the DES simulation.............................................................. 29 3.5.5 Steady modelling of a unsteady problem ........................................................................ 30 4 SIMULATION PROCESS ......................................................................................................... 32 5 NUMERICAL PROCEDURE, RESULT AND DISCUSSION............................................... 33 5.1 5.2 5.3 5.4 6 FLOW FIELD IN GENERAL (TIME DEPENDENT ANALYSIS) ........................................................... 34 POSITION 1 [X = 0.14LSUB] ......................................................................................................... 34 POSITION 2 [X = 0.23LSUB] ......................................................................................................... 36 POSITION 3 AND 4 ..................................................................................................................... 39 UUVS AND LARS IN SHORT .................................................................................................. 45 6.1 THE US NAVY UUV MASTER PLAN (UUVMP) ....................................................................... 45 6.2 UUV’S ...................................................................................................................................... 47 6.2.1 Navigation ...................................................................................................................... 47 6.2.2 Guidance and Communication ....................................................................................... 47 6.2.3 Propulsion and Endurance ............................................................................................. 48 6.2.4 Stability........................................................................................................................... 48 6.2.5 Control............................................................................................................................ 49 6.2.6 Categories....................................................................................................................... 52 6.2.7 Discussion....................................................................................................................... 53 6.3 LAUNCH AND RECOVERY SYSTEMS .......................................................................................... 53 6.3.1 Funnel/Cone Recovery Systems ...................................................................................... 53 6.3.2 Belly mounted Stinger / Buoy Vertical Pole ................................................................... 54 6.3.3 Universal Launch and Recovery Module........................................................................ 55 6.3.4 Sea Owl SUBROV........................................................................................................... 56 6.3.5 Boeing Torpedo mounted retractable arm...................................................................... 57 6.3.6 Reverse Funnel Recovery – Authors suggestion ............................................................. 58 7 CONCLUSION ........................................................................................................................... 59 8 FURTHER WORK ..................................................................................................................... 60 5 9 REFERENCES............................................................................................................................ 61 6 Nomenclature Symbol Unit [kg/m3] [Pa s] [–] [s] [m/s] Description Density Viscosity Under relaxation factor Time step Turbulent inertia tensor x , Lcell B CD CFL D F FB g G, CoG IXX K2 LAR, LFR Lsub LUUV M p p* [r/s2] [r] [m/s] [m] [–] [–] [–] [m] [N] [N] [m/s2] [–] [m4] [–] [m] [m] [m] [–] [Pa] [Pa] p´ [Pa] Angular acceleration roll Euler angle of roll Velocity of fluid Grid/Cell size Centre of Buoyancy Axial Force Coefficient Courant-Friedrich-Lewy Diameter Force Buoyancy force Gravity Centre of Gravity Mass moment of inertia, roll Form factor by Jackson Section Length Length of submarine Length UUV Metacentre Pressure Guessed pressure Correction pressure, Fluctuating component of pressure Improved pressure Reynolds number Strouhal number (~0.2) Free stream velocity of fluid Maximum velocity of fluid Cell volume Kinematic viscosity Height of sail Boundary layer thickness t uiu j p v , [u,v,w] new p Re St U∞ Umax V v zsail δ [Pa] [–] [–] [m/s] [m/s] [m3] [m2/s] [m] [m] 7 Acronyms and Abbreviations ADCP API AUV AUVG CAD CFD DARPA DES DSTO DTMB DTRC ITTC LARS LES NGS RAN RANS ROV UUV UUVMP Acoustic Doppler Current Profiler Application Programming Interface Autonomous Undersea Vehicle Autonomous Undersea Vehicle Glider Computer Aided Design Computational Fluid Dynamics Defence Advanced Research Projects Agency (US) Detached Eddy Simulation Defence Science and Technology Organisation David Taylor Model Basin David Taylor Research Center International Towing Tank Conference Launch and Recovery System Large Eddy Simulation Next Generation Submarine Royal Australian Navy Reynolds-Averaged Navier-Stokes Remotely Operated Vehicle Unmanned Undersea Vehicle United States UUV Master Plan 8 1 Introduction There are two leading trends in the submarine and military industry that are growing rapidly. The first one is to put more of the payloads outside the pressure hull on the next generation submarines. The second one is to increase the safety of the personnel by using autonomous vehicles on dangerous tasks, such as mine counter measurement and Intelligence, Surveillance and Reconnaissance missions, rather than humans. Due to this there is an interest in conducting an investigation of where and how an Unmanned Undersea Vehicle (UUV) could be recovered to a submarine. A submarine displaces thousands of tonnes of water and is surrounded by turbulent fluid while travelling through the water. Why a study of the wake and the fluid around the submarine is needed to fully comprehend the difficulties involved in recovering a UUV to a submarine. Hence, the goal of this study is to investigate whether a recovery of a UUV at speed is feasible, by its own control or with help from a Launch and Recovery System. The investigation is performed by conducting a series of simulations of an UUV docking to a submarine using a Computational Fluid Dynamics (CFD) tool. Using a CFD tool is cost efficient compared to full scale experiments but the results from the simulations needs to be verified to some degree by experimental data. 1.1 Scope The goals of the study which is outlined on a requirement specification given by ASC Pty Ltd to the author are as follows: What the effect the boundary layer around the submarine, and the wake trailing the sail, has on the UUV. Where on the submarine is a recovery is most favourable? Whether these forces are so large that the submarine cannot compensate for them itself? How a Launch and Recovery System should be constructed to accommodate the need for a safe docking procedure. The report focuses on the complexity of the flow surrounding a submarine and the difficulties simulating it. The reader will get a general explanation how the flow field around a generic submarine develops and later presented with the results from full sized computer simulations with a UUV in close proximity to the Submarine. A literature study containing detailed information about UUVs and Launch and Recovery Systems (LARS) is presented to the reader. In these chapters different types of UUVs and LARS are identified and categorised. The study is conducted to highlight present and past problems with UUV recovery procedures. 1.1.1 Limitations There are a few limitations that were decided on during the literature study; 9 The submarine model that all simulations are conducted with is decided to be similar to a normal sized diesel electric submarine or more specifically 87.12 meters in length and 10.1 meters diameter. During the literature study it was identified that most submarines cannot, or are reluctant, to travel below 2 knots. At the same time most UUVs cannot exceed 5 knots. Therefore a single recovery speed of 3 knots is chosen. There was originally intended that a set of simulations where to be made for different angles of attack for the submarine to the free streaming fluid. However only one set of simulations is made at a zero degree angle of attack. Because of limitations in the CFD tool only simulations of static problems are made. Further limitations and constraints concerning the modelling of the problem in the Computational Fluid Dynamics software will be explained in chapter 3. 10 2 Approach to the Fluid Dynamic problem In order to determine the best location for recovery it is necessary to know how a flow field around a submarine behaves. One way of achieving this is to construct a scale model of the body in question and conduct a series of flow experiments. This is a time consuming, expensive but well-established approach. In recent decades however, with the exponential increase of computing power and improvements in numerical algorithms, Computational Fluid Dynamics (CFD) has gained increasingly favour. Using CFD an operator can relatively straightforward construct a virtual towing tank or wind tunnel. Used in conjuncture with Computer Aided Design (CAD) the operator can construct and modify complex geometries and perform a series of simulations covering a wide range of flow conditions. A warning hand is raised though; it is an easy pitfall to think that CFD is the solution to all fluid dynamic problems. Still even with increasingly computing power a direct numerical solution of a problem will probably not be feasible until earliest 2080, (Spalart, 2000). To overcome this problem a lot of different approaches to model the turbulence and average solutions has seen the light of day. 2.1 The Model The DTMB model 5470 configured with bare hull and sail as the only appendage is used as the starting point. The aft control surfaces are omitted from the model as they are considered not to have any significant effect on the UUV, whereas their inclusion would negatively impact on the computer resources required. Figure 1 show the geometry used during this study. The model used in the simulations is scaled twenty times in order to mimic a diesel electric submarine displacing about 7000 tons. Further discussion of the effect of scaling is contained in section 3.5.1. The questions asked and answered during this study is: 1. What is the most favourable location on the submarine to launch and recover a UUV? 2. What characteristics does the flow around submarine take at “recovery speed”? 3. What pressures and velocities act on the UUV in the turbulent wake and boundary layer of the submarine? Question 1 and 2 can relatively easily be extracted from a steady-state simulation using a CFD code. Question three however is more challenging. Ideally one would use an overset grid approach, (CFD-Online, the free CFD reference, 2006), which would allow the two bodies to move through the computational space independently of one another. Unfortunately, such facilities are not yet readily available in commercial CFD codes. Therefore, for each recovery position, a series of steady-state simulations were performed with the UUV located at various positions along its trajectory. The process was automated by writing a Java macro script to perform the processing required at each point on the trajectory, and running the various simulations sequentially in batch mode using a Python script to control the process. The procedure is described further in chapter 4. 11 2.2 The DARPA SUBOFF Project It is essential to be able to verify the results gained from the simulations. One way is to compare the results with experiments made in controlled environments, such as a wind tunnel or towing basin. Therefore information is available in the public domain from experiments performed on hulls, airfoils and submarines. In this study the DARPA SUBOFF Project is chosen for validating purposes. The Defence Advanced Research Projects Agency (DARPA) is the central research and development organization for the United States Department of Defence. In the end of the 1980’s there was an initiative taken by DARPA to develop an experimental database for CFD code validation. The experiments were held at the David Taylor Model Basin (DTMB) in Bethesda, Maryland. Two models were built, DTMB Model no. 5470 and 5471, which differed only in the location of the surface pressure taps. Model no. 5470 was designed for towing tank experiments while model no. 5471 was designed for the wind tunnel. The details of the models and their configurations are described in (Groves, Huang, & Chang, 1989). 2.2.1 Axisymmetric Hull The DARPA models have an axisymmetric hull with an overall length of 4.356 m and a maximum diameter of 0.508 m. The characteristic length used to reduce the results to non-dimensional form is 4.261 m or ~0.978 L. The hull is composed of a fore-body, a parallel middle-body, an after-body, and an aft-body cap of 1.016 m, 2.229 m, 1.111 m and 0.095 m respectively, see Figure 1. Full geometrical details are contained in (Groves, Huang, & Chang, 1989). The coordinate system adopted in the present study is shown in Figure 17. Figure 1 – DTMB model no. 5470, Hull + Sail configuration 2.2.2 Sail The sail is located on the hull at top dead centre with its leading edge positioned at x = 0.924 m (.2121 Lsub) and trailing edge at x = 1.293 m (.2968 Lsub). A cap is attached to the top of the sail at height of 0.460 m (zsail), from the hull, and is a 2:1 elliptical cross-sectional shape. The sail and cap profile are found in (Groves, Huang, & Chang, 1989). 2.3 Governing equations The governing equations for fluid flow, which describe the conservation of fluid mass and momentum, are the equation of continuity and the Navier-Stokes equations. The derivation of the Navier-Stokes equations begins with the conservation of mass, 12 momentum and energy being written for an arbitrary control volume, and can be followed in full in (Versteeg & Malalasekera, 2007). If we instead consider that we have an incompressible Newtonian fluid with constant density, ρ, and constant viscosity, μ, then we can express the Navier-Stokes equations in its most general form by equation (12.1), v v v p 2 v g t (12.1) where v is the flow velocity vector and p the pressure. The Navier–Stokes equations are strictly a statement of the conservation of momentum and to fully describe the fluid flow you need more information, boundary conditions etc. Regardless of the assumptions made, a statement of the conservation of mass is generally necessary. This is achieved through the mass continuity equation, given in its most general form for an incompressible fluid in equation (12.2). v 0 (12.2) 2.4 Flow around a submarine Before delving into the numerical approach to fluid dynamics an overview of the flow around a submarine is explained. When an object travels through water it displaces water. This in turn constructs complex flow patterns around the submarine as whole but also the obstacles that are attached to the hull, such as the tower, arrays etc. 2.4.1 Boundary layer In this study all simulations are conducted at a Reynolds number is in the order of Re ≈ 150E6 for the submarine, hence the submarine are surrounded by a turbulent boundary layer. The axisymmetric and slender shape of the submarine prevents the boundary layer from separation until it reaches the negative shaped after-body. 2.4.2 Tip and Junction flows at the sail Junction flow occurs when the boundary layer on a surface encounters an obstacle attached to that surface, (Simpson, 2001). The resulting flow fields are complex and feature three-dimensional separating flow. The stream wise adverse pressure gradients cause the boundary layer to separate and form multiple horseshoe vortices. Figure 2 shows a schematic view of a simplified junction flow and wing tip vortex shedding. The separation line that wraps around the sail has its origin at a stagnation point in front of the sail. The stagnation point is the separating point between the relatively undisturbed flow upstream of the obstacle, and the complex flow region that develops around and downstream of the obstacle. Generally these vortices are highly unstable and break up to form a highly turbulent wake downstream of the obstacle. The vortices that trail from the top of the sail arise from separating flow that occurs as a result of the adverse pressure gradient downstream and upstream flow regions. These vortices are referred to in the following discussion as “wing-tip” vortices. 13 Figure 2 – Simplified illustration of the flow around the sail 2.5 Choice of positions Initially three candidate positions where selected. After assessing the output data from these simulations, the strength of the tip vortices was found to be greater than expected and it became apparent that further information of the wake characteristics was needed. Therefore the investigation was extended to include one extra recovery position aft of the sail, and also to include an un-steady simulation with no UUV present, in order to fully understand the wake characteristics and flow aft of the sail. The resulting four recovery positions are shown in Figure 3. Figure 3 – The positions on the Submarine where recovery simulations where made. It was concluded at an early stage that it would be inadvisable to consider any recovery positions in the aft part of the submarine due to the adverse flow characteristics present in this region. As shown in (Huang, et al., 1992) the stern part of the submarine is dominated by a quickly thickening boundary layer and two contrarotating vortices. The thickening boundary layer is the result of the separation of the boundary layer that occurs due to the adverse pressure that develops from the point 14 that separates the middle body and aft part of the submarine, as explained in chapter 2.4.1. Figure 4 – Presentation of velocity profiles and an approximate illustration of the thickening boundary layer in the aft region. Based on data extracted from velocity profiles at x = [75 80 85 90 95] per cent of model length. Figure 4 further shows that the boundary layer thickness upstream of the afterbody of the submarine does not exceed 0.6-0.9 meters, which is in good agreement with predictions made by the Power-Law theory for turbulent boundary layers on two dimensional flat plates, as formulated by Prandtl (White, 1991). This expression estimates a boundary layer thickness of about 0.55 meter in this region. The power law relationship takes the form: . 0.16 x 1 0.55m (12.3) Re x 7 Further upstream within the wake the sail, the flow is dominated by two contra rotating horseshoe vortices close to the hull, accompanied by two tip vortices. The nature of the flow within this region is shown clearly in Figure 5, and the existing vortex structures could potentially cause a problem for the recovery of UUV’s within this region. Since there are clear logistical advantages in launching and recovering a UUV within this region, a decision was made to investigate the resulting flow forces on a UUV deployed within this region. 15 Figure 5 – Vortices generated by the sail at x = 0.5L, illustrated as in-plane velocity i.e. u = 0. The white streamlines together with black arrows define the direction and the colour the velocity of the fluid. 16 3 CFD and the Star-CCM+ code Computation Fluid Dynamics provides a means of simulating flows of moderate complexity using computational methods, generally without recourse to experimental techniques. A CFD code comprises three main elements: a pre-processor, a solver and a post-processor: Pre-processor Pre-processing is the part where an operator defines the geometry of the region; the computational domain of the model. Furthermore a discretization of the problem is necessary because the partial differential equations that describes a fluid flow are non linear and an analytical solution is almost never present, which is why the domain is divided into a number of smaller subdomains, often referred to as a mesh (or grid) of cells. The problem can hereon after be solved numerically over the grid. A selection of what physical or chemical phenomena that needs to be modelled has to be made and finally define the fluid properties and appropriate boundary conditions. Solver The most well-established numerical solution technique is the finite volume method. Its numerical algorithm first discretizes the integral form of the governing equations and applies the discrete versions to each cell. The objective is to obtain a set of linear algebraic equations, with the total number of unknowns in each equation system corresponding to the number of cells in the grid. The resulting equations are then solved by an iterative method. Post-Processor A Post-processor gives the ability to visualize the solution by different kinds of plots, both 2D and 3D. Also many CFD codes include animation tools for dynamic result display. 3.1 Star CCM+ (the code) The code used during this study is the Star CCM+ (version 3.04.008) from CD-Adapco. Star CCM+ use an “Algebraic MultiGrid Semi-Implicit Method for Pressure-Linked Equations solver” (AMG SIMPLE) when solving the discretized linear system iteratively. Star CCM+ also provides a powerful semi-automatic meshing tool which allows the operator to generate both surface and volume mesh. The mesh is automatically generated upon the operator’s inputs and are valid and of good quality. Furthermore Star CCM+ has the ability to automatically wrap surfaces in order to ensure a complete closed model. 3.1.1 The mesh The volume mesh is the mathematical description of the space or geometry of the problem, (CD-adapco, 2008). It consists of three basic mesh entities, vertices, faces and cells. Where, a vertex is a point in space defined by a position vector. A face comprises an ordered collection of vertices such that they define a surface in threedimensional space and a cell is an ordered collection of faces that define a closed volume in space, se figure 6. 17 Figure 6 – Illustration of vertex, face and cell respectively One of the hardest and most time consuming parts of a CFD simulation is the mesh generation. The refinement of the mesh has a major effect on the accuracy of the solution and one could say that the greater amount of cells the better chance of obtaining a good result. Though the denser the mesh the more computing power and time it takes to generate and calculate the problem. Furthermore the mesh also needs to be valid, no open faces, and of high quality to produce an accurate solution. A non uniform grid is almost always the optimal one with a denser mesh at complex areas and a coarser one in other areas. An example of a non uniform grid is shown in Figure 7. Figure 7 – Non uniform grid However, it is getting more common with intelligent meshing tools that are able to, with relatively little human intervention, construct high quality valid meshes. Star CCM+ offers three different types of volume mesh; tetrahedral, polyhedral and trimmed mesh. The tetrahedral meshing model use tetrahedral shaped cells and is the model that is fastest and uses the least amount of memory out of the three provided. However, the tetrahedral model needs approximately five to eight times more cells to produce the same accuracy as the equivalent polyhedral or trimmed cell mesh. The polyhedral meshing model use polyhedral shaped cells and provides the operator with a balanced solution for complex mesh generations problems. As for the tetrahedral model, the polyhedral mesh model is directly dependant on the quality of the starting surface triangulation. In other words, a bad quality starting surface will lead to a bad quality volume mesh. The trimmed cell mesher provides a robust method of producing a high quality grid that consists of predominantly hexahedral cells with trimmed cells next to the surface. It combines a hexahedral mesh with automatic curvature and proximity refinement and, most importantly, surface quality independence in a single meshing scheme. Of the three models the trimmer meshing model is more likely to produce a good quality 18 mesh for most situations, which is why it was chosen for this study. In Figure 8, the three types of mesh models are illustrated. Figure 8 – Three types of volume meshing, from left to right; tetrahedral, polyhedral and trimmer respectively. Image Copyright© CD-Adapco. 3.1.2 AMG SIMPLE Solver The SIMPLE solver was originally put forward by Patankar and Spalding in 1972 and is essentially implementing a guess-and-correct procedure. A short description of the algorithm will now follow, for a complete derivative of the SIMPLE algorithm see (Versteeg & Malalasekera, 2007). A SIMPLE calculation is initiated by first guessing a pressure field p*. Then by using the discretized momentum equation and the guessed pressure field it yields the velocity components v*, where v* is the guessed velocity field vector in a Cartesian system. After which a correction p’ as the difference between the correct pressure field p and the guessed pressure field p* is defined, so that; p p * p (13.1) A similar definition is done for the velocity field with v’. The correct pressure and velocity fields in the governing equations are substituted for equation (13.1) and by using the discretized continuity equation the mass fluxes at all faces are calculated. The continuity equation is then rewritten so the pressure correction coefficient p’ can be extracted. The new pressure field is then calculated by correcting the “old” one with the newly extracted correction factor. However, the solution is prone to diverge unless some under-relaxation is used during the iterative process so the new, improved, pressure pnew are obtained with; pnew p * p (13.2) Where, ω is the under-relaxation factor for pressure. Usually the under-relaxation factor is changed over the total time of simulation. A ω equal to one is often too large when the guessed pressure field p* is far from the final solution, which is why the operator normally start with a low under-relaxation factor and gradually increase it to one. With the new pressure field a corrected mass flux for the faces are calculated, and from the mass flux the corrected cell velocities can be obtained with; v new v * 19 V p a vp (13.3) Where, p’ is the gradient of the corrected pressure, a vp is the vector of central coefficients for the discretized linear system representing the velocity equations and V is the cell volume. Star CCM+ uses a Multigrid method spanning the SIMPLE solver to speed up the process of finding a solution. Instead of visiting each cell in sequence and updating the values of pressure and velocity a Multigrid solver agglomerates cells to form several coarse grid levels. It then performs a number of cycles with the SIMPLE solver over the original fine layer (known as smoothing). After which the solution is transferred to the next in line coarser level (known as restriction) where the cycling is repeated and yet again the residuals are transferred to the next in line coarser grid level. The restriction process continues until the Multigrid solver reaches the coarsest level, where it turns and repeats the process of transferring solutions and performing the cycles, but to the finer level (known as prolongation). The solution is prolongated until the finest level is reached and the whole process is repeated until satisfactory convergence is reached, se Figure 9. Figure 9 – Schematics of a Multigrid process There are two branches of Multigrid methods; Full Geometric Multigrid and Algebraic Multigrid. Star CCM+ use the latter branch and it has the advantage of performing the agglomeration without taking the geometry into account from the finest level. In other word, the new coefficient matrix representing the coarser levels consists of specially chosen coefficients from the original grid which means that no new discretization is required and the grid does not need to be stored in the virtual memory. 3.2 Reynolds-Averaged Navier-Stokes (RANS) The numerical solution of the Navier-Stokes equations for turbulence in an incompressible Newtonian fluid with constant viscosity is extremely difficult to solve for and it take an almost indefinite fine mesh to find a solution which means that the computational time becomes infeasible for calculation. To counter this, time-averaged equation such as the Reynolds-Averaged Navier-Stokes equations are used in practical CFD applications when modelling turbulent flows. The RANS equations can be obtained by decompose the velocity and pressure into a mean and fluctuating component, equation (13.4); v v v p P p 20 (13.4) where v and v´ are the mean (time-averaged) and fluctuating velocity vectors in a Cartesian system, and P and p´ are the mean and fluctuating component of pressure. By substituting these expressions into the continuity equation, (12.2), and take the time average of the entire equation we get (13.5), v 0 (13.5) where, v is the time-averaged velocity component in a Cartesian system. If we now attempt the same procedure and substituting (13.4) into the nonlinear Navier-Stokes equations, (12.1), and use the time average, we obtain equation (13.6). v v v p 2 v g uiuj x j t (13.6) Thus the mean momentum equation has an additional term involving the turbulent inertia tensor uiuj also known as the Reynolds Stress tensor. This term is never negligible in any turbulent flow and is the source of the analytical difficulties because its analytical form is not known a priori. Essentially the time averaging has added nine new unknown variables (tensor components) that can be defined only by detailed knowledge of the turbulent structure, which is not known. The problem being that the Reynolds stresses are not only related to fluid physical properties but also to local flow conditions such as; velocity, geometry, surface roughness and upstream history, and no physical laws are available to resolve this dilemma, (White, 1991). One way to get around this dilemma is to model the turbulence by using an appropriate turbulence model. 3.3 Turbulence Models As discussed above, the challenge with acquiring a high-quality solution by using the RANS equations is to model the Reynolds stress tensor satisfactory. This is done using turbulence models. It is widely acknowledged that turbulence models are inexact representations of the physical phenomena being modelled and no single turbulence model is the best for every flow simulation, (CD-adapco, 2008). Star CCM+ come bundled with four major classes of turbulence models Spalart-Allmaras models are a good choice for applications that has mild separation and a largely attached boundary layer. A typical example is a flow over a wing K-Epsilon models provide a good compromise between robustness, computational cost and accuracy. Generally well suited for applications that contain complex recirculation, with or without heat transfer. K-Omega models are similar to K-Epsilon models but have seen most application in the aerospace industry, and are therefore recommended as an alternative to the Spalart-Allmaras models for similar types of applications. Reynolds stress transport models are the most complex and computationally expensive models of the four. They are recommended for situations in which the turbulence is strongly anisotropic. 21 From works by and discussion with Dr. Patrick Marshallsay at ASC Pty Ltd the Abe-Kondoh-Nagano (AKN) Low-Reynolds K-Epsilon model was chosen as the turbulence model for the simulations during this study. The AKN model is developed to be used when calculating complex turbulent flow with separation and heat transfer. The simulations done by Dr. Marshallsay showed that the AKN model performed well in comparison with other turbulence models. 3.4 Detached Eddy Simulation (DES) RANS together with turbulence models suffers from the inexact representation of the time-dependent physical phenomena. A different approach is using Detached Eddy Simulation, which is a hybrid modelling approach that combines features of Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES)1. DES uses a RANS solution in regions close to solid boundaries as well as where the turbulent length scale is smaller than the grid dimension and treat the rest of the flow in a LES manner. Therefore a DES model is not as demanding as a pure LES and reduces the cost of computation. However just as in any CFD model DES is not an answer to all turbulence problems; it must be cautioned that the creation of suitable grids is a difficult task. Hence, it needs a lot of careful preparation to run a DES simulation with special care taking when considering mesh size and time step, further discussed in chapters 3.5.3.2 and 3.5.4. 3.5 Uncertainty analysis of the problem and code The ITTC (International Towing Tank Conference) recommended procedures from 1999, (ITTC, 1999), contain guidelines for a general uncertainty analysis in CFD. It is divided into four parts: 1. Preparation; which involves the selection of the CFD code and the specification of objectives, geometry, conditions and available benchmark information. 2. Verification; which amongst other is defined as a process for assessing simulation numerical uncertainties. This includes a grid dependence study and, for a transient solution, a time-step dependence study. 3. Validation; which is defined as a process for assessing simulation modelling uncertainty by using experimental data as a reference. 4. Documentation; which is a detailed presentation of the CFD code (equations, initial and boundary conditions, modelling and numerical methods), objectives, geometry, conditions, verification, validation and analysis. This study is sponsored by ASC Pty Ltd and a continuation of a previously conducted work by Dr. Patrick Marshallsay. Therefore much of the preparatory work contained in the ITTC recommended procedures is taken from the work made by Marshallsay. In (Marshallsay, 2008) Marshallsay compares data extracted from simulating a 1 Large Eddy Simulation model is a time-dependent simulation which implicates Kolmogorov’s theory of self similarity that the large eddies of the flow are dependent on the geometry while the smaller are more universal in character. Thus an explicit solution of the large eddies is possible while the smaller eddies can be solved implicitly using a subgrid-scale model (SGS). (Versteeg & Malalasekera, 2007). 22 DTMB model no. 5470, using only a bare hull, with data from experiments in (Roddy, 1990) and (Huang, et al., 1992). Two different turbulence models were assessed, the v2-f model and the SST k-ω model. The results, shown in Figure 10 and Figure 11, show that predictions of skin friction and surface pressure coefficients made by the SST k-ω model are in close agreement with the experimental measurements undertaken at DTRC. The results from the v2-f model on the other hand are clearly unacceptable. This latter model is known to suffer from realizability problems, (Svenningsson & Davidson, 2003), and is arguably not yet sufficiently mature for industrial applications. Figure 10 – Comparison between Skin Friction Coefficient estimated using CFD and experimental measurements made at the David Taylor Research Centre (DTRC),(Marshallsay, 2008). Figure 11 – Comparison between Pressure Coefficient distribution estimated using CFD and experimental measurements made at the David Taylor Research Centre (DTRC),(Marshallsay, 2008). As explained in chapter 3.3 the author used the AKN k-ε turbulence model described in (Abe, Kondoh, & Nagano, 1993) rather than the SST k-ω turbulence model. This was decided after personal communications with Dr Marshallsay who found that the 23 data collected from the AKN k-ε model simulations are in closer agreement with experimental data than the data from the SST k-ω model simulations. 3.5.1 Scaling of CFD model In order of reducing the scale errors when calculating the forces and moments that act on a UUV when it enters an area in near proximity to the submarine all simulations was made in as near full size scale as possible. After consulting the supervising group at ASC Pty Ltd (Dahlander, Williams, & Marshallsay, 2008) it was concluded that an optimal size is most likely longer than the Collins class, which extends 77 meters, but less than 100 meters long. Scaling is done either by keeping the Froude’s number or the Reynolds number static for both the model and full-scale submarine. The Froude’s number is derived from wave resistance and therefore not applicable in this case, why scaling using a static Reynolds number is implemented. Roddy concludes in (Roddy, 1990) that scale effects between models and full-scale submarines are negligible if experiments are made at or above a Reynolds number of 10E6 – 15E6. Scaling the DTMB model twenty times the size of the submarine reaches 87.12 meters, which in turn means that the Reynolds number exceeds 10E6 – 15E6 as long as you keep the speed of the free flowing fluid above ~0.2 m/s. Scaling the SUBOFF model twenty times generates a Reynolds number of roughly Re ≈ 150E6 if one use a inflow speed of u = 1.54333 m/s, which equals 3 knots. To maintain Reynolds number for the smaller model an inflow speed of u = 31.618 m/s is needed. The drag of the two models is compared in order to verify the scaling of the submarine model. Table 1 displays the resulting comparison between the two simulations. Table 1 – Comparison of Axial Force Coefficient Re ≈ 150E6 Axial Force Coefficient Fpressure Fshear C D 1 2 ( ref vref L2 ) 2 Model Full-scale 0.790E-3 0.799E-3 Figure 12 and figure 13 shows the pressure- and skin friction coefficient distribution over the hull at the lower mean line for both the Full-scale and model simulations, respectively. When compared it is clear that the scaling effects are negligible. 24 Pressure Coefficient at Re 150E6 1 Fullscale Model 0.8 Cp = p-pref/0.5refv2ref 0.6 0.4 0.2 0 -0.2 -0.4 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Distance from bow [x/L] 0.8 0.9 1 Figure 12 – Pressure coefficient distribution at the lower mean line for the model and full-scale. Skin Friction Coefficient at Re 150E6 -3 3.5 x 10 Fullscale Model 3 Cf = w/(0.5refv2ref) 2.5 2 1.5 1 0.5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Distance from bow [x/L] 0.8 0.9 1 Figure 13 – Skin friction coefficient distribution at the lower mean line for the model and fullscale. 3.5.1.1 Drag predictions The drag coefficient extracted from the simulations of the SUBOFF differ with ~5% from the data collected in (Roddy, 1990) during his towing tank experiments. Even though Roddy have not presented any uncertainty analysis for the present configuration of the SUBOFF mode does he however give an approximate margin of error of about 4-10% on the different derivatives of motion on a fully appended SUBOFF model. Moreover in (Pankajakshan, Remotigue, Taylor, Jiang, Briley, & Whitfield, 2003) a margin of error of 10% is presented. 25 The drag coefficient has also been compared to a semi-empirical method proposed in (Jackson, 1992) and differs by a great margin. Jackson’s method is to be used on a submarine that consists of three sections; a super elliptical bow, a parallel middle section and a super parabolic stern, which the SUBOFF model clearly not consists off, Figure 1. Further Jackson’s method uses a form factor, K2, to calculate the drag due to pressure distribution throughout the hull. The form factor being a function of the shape functions and wetted surface coefficient of the different sections respectively, equation (14.1). K 2 ( LAR LFR ) - LAR Cws , A - LFR Cws , F , where LiR Li , and Di Cws,A (14.1) Aws ,i Di Where, LAR and LFR is the length of the sections, respectively. Di is the maximum diameter for the section and Aws,i, is the wetted surface area for the section. The subscript ‘i’ denotes the current section. In table 2 a comparison is shown with the different methods used. Table 2 – Comparison of Axial Force Coefficient. Axial Force Coefficient Roddy RANS K-ε AKN Jackson CD 1.160E-3 1.101E-3 10.69E-3 3.5.2 Presentation and reduction of Data The data is either presented in tabular form or in a plot. The tabular data is rounded down to three working decimals. The force and moment coefficients presented in chapter 5, Numerical Procedure, Result and Discussion, are all averaged over fifty iterations of raw data. This is done because the forces and moments acting on the vehicle did not converge at every single simulation. An example of this is shown in Figure 14 where the top row contain all data collected from one of the simulations conducted aft of the sail. The lower row on the other hand holds the last 50 iterations from where the mean value was calculated. 26 x 10 Lift Force Coefficient Position 17 -4 4 -4 -6 -8 0 -1 0 200 -4 x 10 400 600 Iterations 800 1000 Lift Force Coefficient Position 17 200 x 10 400 600 Iterations 800 -2 Side Force Coefficient Position 17 6.4 750 x 10 800 850 Iterations 900 950 5.8 700 1000 Yaw Moment Coefficient Position 17 750 -5 7.4 2.6 -2.7 6.6 6 -6 -2 6.8 6.2 -3.5 700 1000 Pitch Moment Coefficient Position 17 7 -3 0 x 10 7.2 -2.5 -5 2.8 -5 7.4 -1.5 -3 -4 Yaw Moment Coefficient Position 17 -1 1 -2 -10 x 10 -0.5 Moment Coefficient Force Coefficient Force Coefficient -5 0 2 -2 -2.65 Side Force Coefficient Position 17 3 0 -12 x 10 Moment Coefficient -4 2 x 10 800 850 Iterations 900 950 1000 Pitch Moment Coefficient Position 17 7.2 -4 2.4 7 2.2 -2.85 2 1.8 1.6 1.4 Moment Coefficient -2.8 -6 Moment Coefficient Force Coefficient Force Coefficient -2.75 -8 -10 6.8 6.6 6.4 6.2 1.2 -2.9 -12 6 1 -2.95 950 960 970 980 Iterations 990 1000 0.8 950 960 970 980 Iterations 990 1000 -14 950 960 970 980 Iterations 990 1000 5.8 950 960 970 980 Iterations 990 Figure 14 – Example of data reduction for a simulation 3.5.3 Grid size and dependence study A grid dependence study is necessary for validation that the amount of cells in the grid yield a close enough solution of the problem. It is however a delicate procedure of choosing just the right amount of cells that the solution is accurate enough but do not take a lifetime to converge. The methodology of a grid dependence study is straightforward. One only has to increase the density of the grid until no significant difference is longer observed in the converged solution. Most of the dependence study has already been done in this study by Dr. Patrick Marshallsay. Marshallsay has in his works concluded that the AKN Low-Reynolds K-Epsilon model with approximately two million cells gives a sufficient solution compared to converging time when conducting simulations on the SUBOFF model. With this in mind this study instead focuses on the grid on and surrounding the UUV. Position 4d was chosen to where a grid dependence study is carried out. At this position the UUV has just entered the heavy turbulent area just aft of the sail. It was chosen because at this position the fluid is very complex and consists of small vortices that can only be discovered with a fine grid. In Star CCM+ one can add volume shapes to the continuum and define grid generation rules for them. A block volume was added spanning the area in front and aft of the sail where the length scales of the grid could be varied. Figure 15 shows this together with a before and after image of the grid. 27 1000 Figure 15 – Before and after image of the added volume shape increasing the density of the grid The characteristic length of the cells in the coarse simulation was set to a cell size of Lcell 4.82 10 3 Lsub 0.42 meter, while the finer simulation used half that size, Lcell 2.41 10 3 Lsub 0.21 meter. The result did show a small difference between the two simulations but judging the fact that the finer mesh used almost twice the computing time to converge, the coarser grid size was chosen. 3.5.3.1 Surface grid problems with the UUV Control Surfaces One problem did arise with the grid. Caution should be taken when using results from simulations where the external force acting on the UUV is weak. The surface grid on the control surfaces of the UUV is not optimal and adds noise in the solution. A solution to this is to remove the control surfaces but they are needed to give the model an accurate representation of an ordinary UUV. 3.5.3.2 Deciding grid size for the DES simulation For the DES to act as a LES and detect all eddies in the wake area of the sail the mesh needs to be fine, but how do one determine what is fine enough? One way of doing it is to analytically estimate the smallest and largest vortices in the wake. It is a rule of thumb that the largest vortices behind a wing can be as long as the cord of the wing, which can be applied here because it is the area behind the sail that is of interest. To 28 determine the smallest ones one can use the Kolmogorov micro scales, which is a theory suggested by Andrey Kolmogorov in 1941, (Versteeg & Malalasekera, 2007). Kolmogorov suggested that the smallest scales of turbulence are universal and that they depend only of the fluids viscosity and the average rate of energy dissipation per unit mass. By using the Kolmogorov scale, equation (14.2), the smallest vortices would be in the order of 1E-5 m. v 3 L 3 U 1 4 7.071 10 19 0.1 1.5433 1 4 1 105 m (14.2) Where v is the fluids kinematic viscosity, δ the boundary layer thickness on the sail and U∞ is the free stream flow. The maximum boundary layer thickness on the sail was approximated using both the analytical power law and a visual measurement in the CFD code to ~0.1 m. The kinematic viscosity used is the default for H20 in the CFD code. Of course using a mesh size of 1E-5 m would create a mesh so fine that it would not be feasible to solve it in this lifetime. Instead after a couple of tries with different sizes a mesh size of 0.14 m in the area aft of the sail was chosen, which created roughly 3.3 million cells. Usually, during a steady simulation, the computing power allowed up to 5 million cells without the simulation being too time consuming but in this case with much iteration over several time steps it was decided that a finer mesh than the one chosen would take too long to solve. This meant that only vortices of a size ~0.14 m or greater was detected by the CFD code. 3.5.4 Deciding the Time-step for the DES simulation Just as choosing a mesh size the selection of time step is an engineering judgment, and a difficult one. The most common approach one would take is suggested in the CFD code user guide, (Cummings, Morton, & McDaniel, 2008), the Strouhal number. The Strouhal number, St, is a dimensionless number for determine cylinder shedding frequency. Normally the St is ~0.2 which is valid for most cylinders ranging in Reynolds number from 100 to 106. Using this approach and with the added “rule of thumb” that one need approximate 5 to 10 iterations for every period one would get a time step of 0.4 seconds, (14.3), f St U 0.2 1.543 0.229 Hz T 4.37 s L 1.35 (14.3) where St is the Strouhal number, U∞ is the free stream velocity and L is a characteristic length, in this case the width of the sail. However because the simulations conducted during this study are run at a Reynolds number of well above 106 and that experimental data has showed that the Strouhal number can reach St ≥ 10 in high Reynolds flow, (Cummings, Morton, & McDaniel, 2008), other approaches of deciding time step where looked at. (Cummings, Morton, & McDaniel, 2008) discuss different approaches used to determine an accurate time step. Cummings et al. also proposed an iterative approach or a poor man’s “steepest descent” method, as they wish to call it, for choosing a time step. In which one compares the wave number (inverse Strouhal number) against 29 several converged solutions with different time steps and grid sizes. The problem with Cummings et al. approach is the time consumption, their experiment needed six simulations before a small enough time step was conceived, all which took 50 CPU hours each to reach convergence, this by using a mere 0.1 million cells and eight parallel processors working together in a cluster. During the present study a cluster of four CPU’s where used and a mesh of roughly 3 million cells, which is why Cummings et al. approach is ruled out as a decider. Further Cummings et al. discuss the approach made by other researchers in the field. (Spalart, 2001) uses the Courant-Friedrichs-Lewy condition (CFL condition), which can be explained as the ratio of the distance a wave-like disturbance travels in a time step to the grid size, Equation (14.4), CFL U max t CFL x t x U max (14.4) where CFL is a non-dimensionalized number, suggested to be approximately one by Spalart for accurate prediction of large eddies. Umax is the maximum velocity measured in the area of interest (normally Umax ≈ 2U∞, where U∞ is the free stream velocity), Δx is the grid size and Δt is the time step needed. Another approach * introducing a non-dimensional time step Δt* ( t t U l , where l is a characteristic length of the vehicle, in this case the length of the sail) is used by (Strelets, 2001), (Görtz, 2003) and (Schiavetta, Badcock, & Cummings, 2007) in their studies of massively separated flows. Table 3 shows the time step required when predicted by the different methods explained above. Table 3 – Comparison between different methods for time step prediction. Method Δt [s] Strelets Δt*= 0.025 Δt* Görtz Δt*= 0.006 .120 0.029 Strouhal Schiavetta Δt*= 0.01 CFL Spalart CFL ≈ 1 0.048 0.045 4.37 St = 0.2 As shown in table 4 the time step predictions by the different models vary quite a lot. The author choose the method suggested by Strelets because the time step was decided to be small enough for accurate prediction of large eddies and still large enough so that the simulation would not take too long2. However, due to an error made by the author the time step was set to 0.13 seconds and not 0.12, this was determined not to have any significant effect on the result of the simulation so no attempts for correcting it where made later. 3.5.5 Steady modelling of a unsteady problem Simulating a clearly unsteady problem with a steady model is strongly recommended against in the user manual of the CFD code, (CD-adapco, 2008). However if used the CFD code will average the results in a similar matter to time averaged results that could be extracted from a proper transient simulation. The problem arising with 2 It took roughly 350 CPU hours, divided over 4 CPU’s, i.e. just under 4 days, to simulate approximately 180 seconds. 30 simulating an unsteady problem with a steady model is that the result from the steady simulation will be equivalent to using an extremely inaccurate time step in transient simulation. Essentially the CFD code will over the iterations use something similar to a local time step that is smaller where the mesh is fine and larger where the mesh is coarse. Hence the results presented below from the steady simulations are to some stage incorrect and should not be treated as an absolute fact. The problem lies within the small unsteady vortices. Even though the primary vortices could be stable to some extent, the secondary or tertiary vortices are unstable and very difficult to average over a period of time. Their contribution in terms of force on the UUV is however small compared to the larger vortices. For this reasons, the force- and momentcoefficients extracted from the simulations are determined to be accurate enough for this investigation. 31 4 Simulation process Star-CCM+ has the ability to be started in macro mode without using the graphical user interface. It requires that the macro scripts are written in Java and the program comes bundled with its own Java Application Programming Interface (API). In order to be more versatile and easier make changes to specific runs several macros is written, each with a specific purpose and input data. Spanning this, a Python script is written to control the sequence of which positions and what type of simulations is performed. The process is visualised in Figure 16. Figure 16 – Overview of the simulation process Where, 1. Translate the UUV to the given position and constructed the grid. 2. A less accurate but converged solution is firstly obtained with a first-order segregated solver and with the under-relaxation factor set to a low value. This is a common procedure if a more accurate converged second-order solution is unobtainable at first, (CD-adapco, 2008). 3. After a converged solution is found the script switches to the more accurate second-order solver and high under-relaxation factors. Thus resulting in an accurate and converged solution. 4. This step extracted coefficients from the solution into raw data files. 5. The data was lastly imported into MATLAB for post-processing. 32 5 Numerical Procedure, Result and Discussion In this chapter all results extracted from the simulations is presented and discussed. All simulations used the same Cartesian coordinate system, with its origin situated at the front tip of the submarine with the X, Y and Z axis directed horizontal positive aft, horizontal positive port and vertical positive up respectively, as shown in Figure 17. All forces and moments coefficients presented below are displayed in this coordinate system, with the force and moment coefficients acting on the UUV at its centre of gravity, which is situated at x = 0.375 LUUV from the front, (Prestero, 2002). Figure 17 – Coordinate system on the REMUS 600 UUV and the continuum as whole, respectively. However when the UUVs distance from the hull is presented, the author uses the distance from body to body. Reason being so the reader can easier tell whether the UUV has entered the turbulent boundary layer or not. The UUV used during the simulations is based on the REMUS 600 with a total length of 3.25 meter and a diameter of 0.35 meter. A total of 26 static simulations have been conducted divided over the four positions discussed in chapter 2.5. For each simulation the UUV had to be placed at its location, after which the continuum was meshed and the solution calculated. After the data was extracted to post processing the UUV was translated to its new location and a new mesh and solution was generated and calculated. All locations simulated at are displayed in Table 4. For position 1 and 2 the distance from the hull is non-dimensionalized by the boundary layer thickness but at positions 3 and 4 the sail height is used. This because at the former locations the boundary layer is the dominant turbulence factor whiles at the latter ones the sail is the origin of the dominant turbulence. 33 Table 4 – Overview of all simulated locations. Note that position 1 and 2 are non-dimensionalized by boundary layer thickness while at 3 and 4 the height of the sail is used. 1 2 3 1/δ a b c d e f g h i j 4.8 3.3 2.5 4 1/Zsail 5.7 2.9 1.5 0.8 1.12 1.05 0.98 0.87 0.54 0.30 0.23 0.11 0.07 1.55 1.12 1.05 0.98 0.87 0.54 0.30 0.23 0.11 0.07 5.1 Flow field in general (time dependent analysis) The simulations presented below are all conducted so both the submarine and the UUV are fixed in space with the fluid flowing around them and a time-averaged solution is calculated. The reason, as explained in chapter 3.5.5, is that the CFD code at the time of this study did not support dynamic meshes and therefore it was impossible to simulate a “live” recovery of an UUV. One consequence of this is that all the calculations of pressure, vorticity and fluid direction is averaged over time, hence it is difficult to draw any definite conclusions how much the force exerted from the fluid on the UUV fluctuates over time. Thus an un-steady simulation with only the submarine present in the continua was conducted. The turbulence model chosen was Detached Eddy Simulation, DES, which in some cases can result in the best of both worlds between Reynolds averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) turbulence models. However the simulation was conducted with a too coarse grid for the DES to function properly. Instead of showing a vortex shedding and turbulence that changed over time a timeaveraged RANS solution appeared. 5.2 Position 1 [x = 0.14Lsub] Position 1 is the only position investigating conditions in front of the sail. This region consists of a laminar flow with a small turbulent boundary layer. At this position the submarine’s hull is cone shaped which produces a favourable pressure gradient that hinders the boundary layer growth. Furthermore the cone shape increases the fluid velocity and decrease the pressure at this position. In theory the best solution would be to control the UUV so that the fluid attacks it head on at all time which minimizes the rudder movements during the recovery procedure. This is however very difficult so the UUV is simulated fixed parallel to the free stream and not the hull, as shown in Figure 18. 34 Figure 18 – The direction of fluid, illustrated by black streamlines, at the bow with UUV at close location to the hull at position 1. In conclusion, three simulations where conducted at this position, at increasing distances from the hull, shown in Figure 19. The distances from the hull to the vehicles centre of gravity and stern are presented in Table 5. The centre of gravity of the UUV is not within the boundary layer at any time but the aft of the vehicle enters the turbulent area in simulation 1c. Figure 19 – The UUV location at the three simulations, respectively, at [x, y] = [0.14Lsub, 0] Table 5 – Distances from the hull where the UUV where situated at position 1 non-dimensionalized by boundary layer thickness δ. a b c CoG 4.8 3.3 2.5 Stern 3.2 1.7 0.9 Figure 20 shows the resulting force and moment on the UUV. As expected the side force- and yaw moments are both very small because of the uniform UUV body. The increase is most likely due to noise. The lift force coefficient shows that the UUV is repelled by the fluid flowing around the bow of the submarine. As the vehicles approach each other a squat effect due to the two objects pressure fields give way to a decrease. A similar conclusion can be drawn for the pitch moment coefficient which increases as the UUV approach. 35 Figure 20 – Force and Moment acting on the REMUS 600 at Position 1. The dots represent one simulation each and the Y Axis shows the distance from the hull of the submarine to the CoG of the UUV. Left and bottom axis are non-dimensionalized. 5.3 Position 2 [x = 0.23Lsub] In these simulations the UUV is positioned next to the submarine’s sail. Except for the horse-shoe vortices and the turbulent boundary layer the region is dominated by a steady non turbulent flow. The sail is situated at the intersection between the bow and the parallel middle section which means that the fluid is still flowing with an angle slightly outward from the centre of the hull, see Figure 21. Four simulations are conducted at this position all located along a straight line at 15 degrees from the upper mean line of the submarine, see Figure 22. The distances outwards from the hull are chosen in relation to the boundary layer thickness at this position and are presented in Table 6. 36 Figure 21 – Direction of the fluid and its magnitude at position 2 – CoG, viewed from aft. The arrows represent the direction of the fluid (u = 0) and the background colour represent its magnitude. Figure 22 – Locations of the simulations at position 2, viewed from front. Table 6 – Distances from the hull where the UUV where situated at position 2 non-dimensionalized by boundary layer thickness δ. a b c d 5.7 2.9 1.5 0.8 The reason why the UUV only partly enters the boundary layer is solely because it is not thick enough and that the UUVs control surface would collide with the hull of the submarine before it would enter the turbulent boundary layer area. 37 In Figure 23 where the forces and moments acting on the UUV is shown one can see that all of the forces and moments are following a distinctive pattern as the smaller vehicle approaches the hull of the Submarine. There is a force repelling the UUV which is increasing until it enters the boundary layer and one of the horse-shoe vortices where a decrease of the force occurs. It is more likely that the decrease is due to the fluids directional change in the horse-shoe vortex than the interaction between the two objects pressure fields. Figure 23 – Force and Moment acting on the REMUS 600 at Position 2. The dots represent one simulation each and the Y Axis shows the distance from the hull of the submarine to the CoG of the UUV. Left and bottom axis are non-dimensionalized. The Side Force Coefficient plot’s shape is similar to the Lift Force Coefficient. In this case the forces acting on the UUV are inflicted by the horse-shoe vortex which at first pushes it toward the sail of the submarine but when the UUV get situated inside the vortex the force decrease again. The Yaw Moment Coefficient is explained by the route the fluid takes around the sail of the hull. The front part of the UUV is located so that the fluid is parallel when it strikes the smaller vehicle, but when the fluid leaves the aft part of the UUV it is drawn to the centre of the submarine due to the shape of the sail. This is clearly shown 38 at the aft of the UUV in Figure 24, where the separation of the fluid is clearly larger on the side facing the sail. The negative Pitch Moment Coefficient is most likely a result of the complexity of the horseshoe vortex as it propagate throughout the hull of the UUV. A slight decrease in the negative moment is visible when the vehicle enters the boundary layer which can be attributed to the pressure field interaction. Figure 24 – Top view over Pressure and Vorticity distribution, respectively, over the UUV (small object) and the sail of the submarine at position 2. Observe that in the lower right image of Figure 24 the origin of the horse-shoe vortex is visualized as a high level of vorticity. 5.4 Position 3 and 4 Position 3 and 4 are both situated aft of the sail of the submarine to answer whether a recovery is plausible at all in this region, maybe at a certain distance aft of the sail. The simulated distances from the submarines hull are directly related to the height of the sail and specified in Table 7. 39 Table 7 – Distances from the hull at position 3 and 4, respectively. Non-dimensionalized by sail height (Zsail = 4.41m). 3 a b c d e f g h i j 1.12 1.05 0.98 0.87 0.54 0.30 0.23 0.11 0.07 4 1.55 1.12 1.05 0.98 0.87 0.54 0.30 0.23 0.11 0.07 Position 3 is located so the UUVs bow is x = 0.3Lsail aft of the sail and position 4 is situated so the UUV has its centre of gravity amidships the submarine. The region aft of the sail is turbulent and dominated by two pairs of contra-rotating vortices; the horseshoe- and “wing tip” vortices which both commence from the sail. This is illustrated in Figure 25 which shows an in plane projection of the fluid, [u,v,w] = [0,v,w], at position 3 and 4 respectively. 40 Figure 25 – Direction of the fluid and its magnitude at position 3 and 4 respectively. The arrows and streamlines represent the direction of the fluid and the background colour represents its magnitude. Figure 26 shows the lift force and pitch moment coefficients acting on the UUV. It is visible that both plots follow a similar pattern but the forces and moments are greater for the position closer the sail. The Lift Force Coefficient plots shows that the UUV is affected by a small downward force when in the free flowing area above the sail. At this distance from the hull the attracting force between the objects due to the pressure field interaction should be next to nothing, therefore the force is most likely due to the noise created by the UUV’s control surfaces, as explained in chapter 3.5.3.1. The most interesting observation is when the UUV enters the tip vortices which then exert 41 a repelling force on the smaller vehicle. This force only affects over a short distance between circa ~1.05 to ~0.7 the height of the sail. It then changes to an attracting force which increases as the vehicle approach the submarine. The attracting force is due to the downward direction of the horse-shoe vortices with a small contribution from the pressure field interaction between the objects. The Pitch Moment coefficient shows a similar behaviour. In theory the UUV should attain an increasing positive trim the closer it gets to the submarine, which it also does. An exception exists when the vehicle pass through the tip vortices where an irregular much larger moment is present. Figure 26 – Lift Force and Pitch Moment at position 3 and 4 respectively. The dots represent one simulation each and the Y Axis shows the distance from the hull of the submarine to the CoG of the UUV. Left and bottom axis are non-dimensionalized. Figure 27 illustrates the interaction between the two objects pressure field. Observe that the dominating low pressure at the stern of the UUV which is causing the positive trim when the UUV is in close proximity of the submarine. 42 Figure 27 – Interaction of pressure fields between UUV and Submarine in close proximity to each other at position 4. From left is front, middle and aft of middle-body shown. 43 Figure 28 – Side Force and Yaw Moment Coefficients at position 3 and 4 respectively. The dots represent one simulation each and the Y Axis shows the distance from the hull of the submarine to the CoG of the UUV. Left and bottom axis are non-dimensionalized. In Figure 28 the Side force and Yaw moment coefficients is presented and it is clearly shown that they are very irregular, almost chaotic. This can be attributed to the complexity of the vortices which changes characteristic and direction throughout the vehicles body as the UUV descends towards the hull. 44 6 UUVs and LARS in short These chapters cover the UUV and LARS technology and their basic theory of control and communication. A short presentation of most UUV’s and LARS is presented and a few is discussed in depth. However a lot of information regarding the different system is company and/or Commonwealth proprietary and is not available to the public. There are multiple UUVs on the market today and their numbers are growing. Earlier there where a clearer distinction between UUV’s for military and civilian use but lately module based systems with the ability to use “off the shelf” products as payload modules are becoming more of a standard. A module concept is not only more versatile but much more cost effective and there are some systems on the market today that are able to conduct a wide variety of functions. An example of a modular based system is the AUV 62 from SAAB Underwater Systems; figure 29 shows the setup for the UUV and all the interchangeable parts. Figure 29 – Example of a module based system, AUV 62 Sapphires in basic configuration, Copyright© SAAB Underwater Systems 6.1 The US Navy UUV Master Plan (UUVMP) In 2004 the US navy released an updated version of its UUV Master Plan, (U.S. Navy, 2004), in which they describe their vision that an UUV can; “Attack today’s littoral coverage problem and tomorrow’s advanced threat” Furthermore an UUV can gather, transmit or act on all types of information, from anywhere to anyone… Deploy or retrieve devices, anyplace, anytime… Engage any target, bottom, volume, air or space. With minimal risk to US force… at an affordable cost. Most importantly is of course the cornerstone where cost is not necessarily monitored in the monetary value of the UUV but also the cost of human lives. Further the Master Plan categorise UUV/AUV’s into four vehicle classes depending on their size, which is shown in Table 8. 45 Table 8 – Vehicle classification according to the US UUVMP Man Portable Light Weight Vehicle Heavy Weight Vehicle Displacement 10-50 kg ~250 kg ~1000 kg ~10 000 kg Endurance 10-20 h 20-40 h N/A N/A Shape / Diameter N/A Torpedo 12.75 in. Torpedo 21 in. N/A Class Large Vehicle The Man Portable class is omitted from this study because firstly its endurance is determined not sufficient for deployment into littoral zones from a submarine, and secondly that the Master Plan only identifies the three larger classes as deployable and recoverable from a submarine. The Large Vehicle class is intended to be used in AntiSubmarine warfare missions thus carrying heavy torpedoes which is why it is simply too large and heavy to be carried by a medium/large sized diesel electric submarine. Hence it is omitted from the study. So, why are UUVs a necessary force multiplier for a Navy? Well, except for being able to operate in deniable areas there is an obvious important fact; “Minimizing human casualties during hazardous missions” Additionally the Master Plan has identified nine functions in which the UUV’s are superior in use. Four of them however are solely for the large- and man portable class vehicles and therefore not presented. The five remaining, with a brief explanation, in prioritized order are; Intelligence, Surveillance and Reconnaissance (ISR) UUV’s are perfectly suited for information recovery due to their ability to operate undetected in littoral areas extending the reach of their host platforms into previously inaccessible areas. Mine Countermeasures (MCM) It is desirable to minimize risk to a fleet operating in a specific area, to do this time is paramount and it is proven that using a UUV is far more time efficient than any human diver. Oceanography Knowledge of the operating environment is of key importance and conventional data collection is commonly dependent on hull mounted or towed systems. UUV’s permits characterizations of greater areas at less cost and also perform reconnaissance in a near shore environment while its host remain at a safe distance. Communication / Navigation Network Nodes (CN3) A small vehicle has a greater chance to stay undetected while manoeuvring to the surface and using a discrete antenna to communicate. An UUV can also provide a link between a submarine and Global Positioning System (GPS). Information Operations (IO) 46 An UUV could be used either as a platform to jam or inject false data into enemy communication network or secondly as a submarine decoy. An example of this is the AUV 62 from SAAB Systems which can be fitted with a payload module containing noise transmitters and echo responders to mimic the signature of a submarine. 6.2 UUV’s In this chapter a brief explanation of how an UUV works is presented and discussed. This is to give the reader a basic understanding of some of the problem involved with a recovery of an UUV to a submarine whilst at speed. 6.2.1 Navigation All AUVs use an Inertial Navigation System to navigate in submerged mode. The works by utilizing motion sensors and computers to keep track of the vehicles position, orientation and velocity. Usually it is used together with a GPS or another means of getting an initial position. In this specific case the host’s position is most likely be programmed in the AUV before the start of the mission. To easier understand the concept of inertial navigation, one can imagine oneself sitting blindfolded in the passenger seat of a car trying to navigate by feeling the movements of the car. This system is of course not entirely perfect, far from it, and it does experience internal errors. The AUVs then either resurface in intervals to reacquire an absolute position by using GPS, or using an Acoustic Doppler Current Profiler (ADCP) the AUV can bounce sound of the bottom and determine its velocity. According to the University of Southampton their Autosub, which uses this system, has a navigational error of 0.1% per travelled distance (Underwater Systems Laboratory at the National Oceanography Centre, 2007). The Kongsberg group on the other hand claims that their Hugin and REMUS AUVs have a navigational error less than 0.03% when following a lawnmower pattern3. This is possible by using a Terrain Contour Matching navigation system that uses an on board contour map of the terrain and compares it to the image collected by the vehicles sonar system. Another way of aiding the Inertial Navigation System is the use of acoustic beacons. These need to be delivered beforehand at strategic locations or in some cases there are suggestions that the AUV could place the beacons before conducting its mission, and to recover them when finished. By using this approach the AUV is constantly updated with its absolute position which lowers the navigational errors close to zero. However, the alternative with acoustic beacons might not be optimal if ones intention is to stay undetected. 6.2.2 Guidance and Communication When in close proximity to the Submarine the AUV communicates by undersea acoustic modems. One would hope that the AUV could be remotely controlled from the host ship while conducting the recovery, but the low bandwidth and time delays involved with undersea communications currently makes this very difficult. There are however a few Virtual Tether-solutions on the market that claim a bandwidth close to 3 A lawnmower pattern is the name of the movement pattern an AUV follows when it is surveying an area, the name given because its resemblance of a person’s movement when moving the lawn. 47 200 Kbits/s. Whether it is failsafe4 enough to actively remotely control the vehicle or not is not known but it is fast enough to work as a real time positioning for the AUV relative the submarine during a recovery procedure. A surfaced AUV can also communicate using the Iridium satellite network or, at a closer range, using a Wireless Local Area Network (WLAN) connection. 6.2.3 Propulsion and Endurance Power consumption is of course directly proportional to the shape of a UUV. A long slender shape is likely to use less energy than a short bulky shape. One consideration has to be accounted for though: the size of the payload. If the payload is square in shape then it may be of advantage to use an UUV with a box-like shape with rounded corners. The circular shape body have to be much larger to contain the payload, with added wetted surface and drag area as a consequence. Most torpedo shaped UUVs have a single propeller at the aft. Some torpedo shaped UUVs use a setup with two contra rotating motor assemblies, this to exert a zero net torque in order to give the possibility of controlling the vehicle roll (Stevenson & Hunter, 1994). 6.2.4 Stability There are two ways for an UUV to maintain a certain depth during its mission. It flies in either auto depth or auto altitude mode. In auto depth it uses the depth sensor to calculate its depth and in auto altitude it uses an ADCP and follows the ocean floor terrain. Auto altitude is by far the most common mission approach. 6.2.4.1 Hydrostatic Stability For a surfaced vehicle we consider the metacentre height as a measurement on how stable a certain ship or surfaced undersea vehicle is but as the submarine, or the UUV, descends it is required, for all transversal and longitudinal, that the centre of gravity is below the centre of buoyancy. It is the size of this distance, BG, which determines the stability of a submerged vehicle. Figure 30 illustrates the changes of B, G and M in a surfaced and submerged condition. Figure 30 – Cross-section of UUV to illustrate the changes in B, G and M between surfaced and submerged condition. There is one great advantage with a torpedo shaped vehicle compared to an “odd” shaped vehicle when considering the hydrostatic stability. If a UUV is subjected to an 4 The AUV will have a fallback mode in case the communication fails for military applications. 48 external force of i.e. vorticity in the wake after a submarine, let us also assume that this force can be simplified as it would be acting on a single point on the UUV. Furthermore this point is directed perpendicular upwards to the longitudinal axis, on a body fixed coordinate system, and situated on the longitudinal centre of gravity. With these assumptions this force would only inflict movement in roll terms of the UUV. We are also assuming that it is a static environment so we can make the following simplifications to the roll equation of motion for an UUV, formulated by (Nahon, 2006), simplified in equation (7.1). FB BG sin F x I XX p assuming static why, F x p 0 B F BG sin (7.1) Where, FB is the buoyancy force, the Euler angle of roll, F and x is the external force and its point of action respectively, IXX is the mass moment of inertia in roll for the UUV and p is the angular acceleration in roll. We have now determined a relationship between the stability of the submerged vehicle and the external force acting on it. If we now incorporate this to a torpedo shaped and an “odd” shaped UUV and have a look at the differences between them, figure 31, we see that for a torpedo shaped the relation is close to two but for this particular “odd” shape it is closer to eight. In this case it would take four times the force to roll the torpedo shaped UUV than it would for the “odd”-shaped one. Figure 31 – Difference between righting moments to an external force between a torpedo-shaped and "odd"-shaped UUV. Figure 31 shows a not so forgiving selection of shape for an “odd”-shaped UUV. The same rectangular shape rotated 90 degrees in either direction would increase the stability significantly. The reason why the “odd’-shaped UUV is depicted this way is because both of the two “odd”-shaped vehicles discussed in this study have this shape. Another reasoning that promotes a torpedo shaped UUV is its hull smoothness. A fluid directed toward an object exerts a greater force if the object is flat and perpendicular than if the object is rounded. 6.2.5 Control By far most common approach for torpedo shaped UUVs is a propeller at the aft and two sets of control surfaces working as rudders, either fitted as a cross or in an 49 inverted Y configuration, see Figure 32. Some systems can be fitted with an extra set of control surfaces at the front for extra manoeuvrability. This leads to the conclusion that there are very few UUVs on the market today with the ability to hover. There are however exceptions: The Archerfish, a single shot mine disposal system from BAE SYSTEMS which instead of a single mounted propeller in the aft has two thrusters mounted on either side of the body amidships. This gives the Archerfish the ability to operate in either hover mode or transit mode. Figure 32 – Example of an inverted Y control surface configuration Another negative aspect with the rudder configuration as above is the time delay involved in controlling the vehicle. The slower the vehicle travels the longer time it takes for the vehicle to respond to a rudder change. This naturally leads to a problem if the vehicle enters a turbulent area. An example of this is shown in the chapter relating “Navigation, guidance and control of the Hammerhead AUV” in (Roberts & Sutton, 2006). In which it took the Hammerhead roughly 45 seconds to stabilize on a course. The Hammerhead was conducting a circle movement at the surface with a constant rudder angle of 20 degrees and the time is measured from when the Hammerhead started its alignment on a specific heading to when it is stabilized. As shown in figure 33 the rudder command is given at approximately 30 seconds and the AUV stabilizes at around 60 seconds, the spike at roughly 125 seconds is a response to a change in the vehicles heading due to surface currents. Figure 33 – Hammerhead AUV controller trial results: (a) rudder deflections generated and (b) Hammerhead heading. Copyright© the Institution of Electrical Engineers 50 An “odd” shaped UUV on the other hand have superior manoeuvrability when compared. This is necessary if one uses the reasoning mentioned above that it needs a lot more control interaction to be stable when conducting its missions. Typically an “odd” shaped UUV uses a set of thrusters at varying locations, instead of a propeller/rudder combination, for control. 6.2.5.1 Ability to maintain depth Most UUV’s incorporate a fixed ballast system i.e. external weights that needs to be calibrated for the salinity and temperature in the mission area. This usually means that when and if the UUV experiences any local variations in the salinity and temperature or external forces in the water it has to travel with an angle of attack, use thrusters or control surfaces to maintain its depth. This of course affects the endurance of the UUV. Another fact to be taken into account is that most of the UUV’s with fixed ballast systems are made slightly buoyant, so if there is a mishap it floats to the surface. This, of course, is a feature that is not desired if your aim is to stay undetected. Another way of maintaining altitude or depth is the system that Autonomous Undersea Vehicle Gliders (AUVG) uses. They have the ability of changing their buoyancy to descend or ascend and while doing so they use wings to create a lift which propels them forward, figure 34. There are two kinds of glider to date, they both have a variable buoyancy system but use different technologies. Figure 34 – Illustration of an Autonomous Undersea Vehicle Glider’s flight through the water. 6.2.5.1.1 Thermal Glider This type uses the thermal gradient that is present in the ocean. The sun rays keep the water warm towards the surface but the water gradually gets cooler at depths, down to 2-4 degrees Celsius. The “Slocum Thermal Glider” from Webb Research Corporation, (Webb Research Corporation), has wax filled tubes within its body. When the sun and the surrounding water heats the wax it expands and pushes a mineral oil into bladders filling them and thus changing the buoyancy of the glider making it sink. When the wax cools of due to the cooler water the oil retracts from the bladder and the cycle is complete. 51 6.2.5.1.2 Electric Glider This system uses a single stroke piston pump which is connected to an electric motor. Then it either uses it to control the amount of seawater in a bladder situated in the free flooding compartment of the AUVG or to transfer a fluid, usually mineral oil, between one bladder in the pressure hull and one in the free flooding part. The “Slocum Electric Glider” from the Webb Research Corporation, (Webb Research Corporation), also has the ability to move its battery pack forward or aft to control pitch. 6.2.6 Categories There are numerous UUV’s on the market and many of them are very similar in shape and size. Therefore, as mentioned earlier the UUV’s are divided into two groups, torpedo- and “odd”-shaped UUV’s. In each chapter a brief presentation of the UUV’s found and an in depth discussion of an UUV of interest is made. 6.2.6.1 Torpedo Shaped UUV’s In Table 9 a list with the torpedo shaped vehicles found during the literature study are presented. Generally a torpedo shaped UUV consists of a bow, a parallel middle section, and an aft section. Most have the same diameter as a torpedo, 21” or in some cases less than that. Very seldom they have the ability to hover but need instead a minimum forward speed of 0.5-1 knot to maintain control. If they don’t maintain this speed they rise to the surface due to the natural positive buoyancy. In some cases they have a set of forward hydroplanes but most of the time they rely on aft rudders, in different configurations. Most of the torpedo shaped vehicles are powered by a brushless energy efficient “off the shelf” DC motor connected to a two bladed propeller, which makes it very energy efficient and many manufactures claim their system can operate autonomously up to and above 50 hours. Name REMUS 600 REMUS 6000 HUGIN 1000 HUGIN 3000 HUGIN 4500 Bluefin 12 Bluefin 21 AUV 62 Sapphires Autosub AUV Mullaya Table 9 – Torpedo shaped UUVs Depl. Size L/D Depth Manufacturer [kg] [m] [m] 240 3.25/0.324 600 885 3.84/0.71 6000 Kongsberg 650 4.5/0.75 1000 1400 5.5/1 3000 1900 6/1 4500 Bluefin Robotics 181.5 3/0.33 200 Corporation 330 3.3/0.53 200 SAAB 1500 7/0.53 200 Uni.Southamton 7/0.9 1600 DSTO ? ? ? End. [hrs] 50 22 24 60 78 +15 18 ? +505 ? Comments As REMUS 6006 6.2.6.2 The REMUS 600 There is one UUV in the torpedo shaped group that is of special interest. Not only because it is owned and in use by the RAN but also because it is of a typical torpedo shape and of a size that would be able to dock to an average sized submarine without any major modifications of the submarine. One major reason is also that the REMUS was first developed by scientists from Wood Hole Oceanographic Institution (WHOI) 5 The National Oceanography Centre in Southampton claims that the Autosub have up to 144 hours endurance in optimal conditions, but Autosub has not yet been on a mission exceeding 50 hours. 6 Information gathered from personal communication with Dr. Francis Valentines at the DSTO. 52 in Massachusetts, USA. Due to this there is a lot of publicly available information on the REMUS control characteristics and different lengths. In 2008 Kongsberg Maritime A/S acquired the rights to construct and sell the UUV. 6.2.6.3 “Odd”-shaped UUVs There are still a few “odd”-shaped UUVs on the market today. No detailed information, on any of the systems, where possible to apprehend even though several attempts were made by the author. A discussion with Dr. Francis Valentines at the DSTO revealed that the Wayamba is decommissioned due to instability reasons. Dr. Valentines also believed that “Odd”-shaped UUVs would more or less be replaced with the torpedo shaped ones. The Talisman from BAE Systems is apparently still under development and the information regarding it is mainly speculations. The information available on public domain at BAE Systems, (BAE Systems), reveals a hybrid diesel propulsion system and endurance up to 24-hours. Lastly the author did manage to sign a non disclosure agreement with SAAB Underwater Systems with the promise that SAAB would supply with detailed specifications, which was unfortunately never delivered. 6.2.7 Discussion In general an “odd”-shaped UUV is very sensitive for external forces and therefore its control systems and acting thrusters needs to be very responsive. This in turn hinders the operating time. In a scenario where the operating time is the weighing factor then the torpedo shaped UUV has the clear advantage. On the other hand if operating time is of less importance and the weighing factor is manoeuvrability then an “odd”-shaped UUV with several thrusters, such as the SAAB Double Eagle SAROV, has the upper hand. A torpedo shaped UUV with a rudder configuration in front of the propeller do not react fast enough to external forces to perform a safe recovery. As of now none of the UUVs are ideal for a recovery procedure and still perform operations at great distances and time from its host. 6.3 Launch and Recovery Systems A number of underwater docking systems have already been developed by the research community and offshore industry. Although most of them are still at a concept or prototype stage the most significant ones are described in this section. 6.3.1 Funnel/Cone Recovery Systems Is by far most common approach to construct a recovery system in the offshore and military market is to have a funnel guiding the UUV into its stowed position. Usually the UUV homes in on the funnel or cone by either sonar or a transponder system using triangulation. All systems on the market today are deployed from surface ships and used in speeds close to nil. Furthermore according to a representative from the DSTO, who has seen a couple of the systems in action on the annual AUV Fest7, claims that they have a pretty low success rate, down to one successful recovery of every ten tries. Another story is told by Stokey in (Stokey, 1997) where it is claimed that the cone recovery system for the REMUS UUV vehicles works well. Figure 35 7 AUV Fest is an annual gathering arranged by NOAA Office of Ocean Exploration and Research, Office of Naval Research and Naval Undersea Warfare Center to demonstrate advanced technology on AUVs. 53 shows an undersea trial and a concept design of a funnel recovery system mounted on a submarine. The concept, developed by the BMT Group, is a dry dock situated on the back of a submarine allowing submariners hands-on handling the UUV while submerged. Figure 35 – Concepts of funnel recovery systems Copyright© BMT Group The advantages with a funnel recovery system is it simplicity and low cost. The negative aspects are that it is a relatively large contraption and that it has yet been proven to work well in non optimal conditions. 6.3.2 Belly mounted Stinger / Buoy Vertical Pole The Belly mounted Stinger, developed by the Florida Atlantic University’s Department of Ocean Engineering, and the Buoy Vertical Pole system, from the Woods Hole Oceanographic institute, works on similar principles. Both systems use a stinger or vertical pole slides in and get caught by a scissor like construction. As shown in figure 36 the Florida Atlantic University’s system have their stinger or pole attached to the underside of the UUV, which in turn interfaces with the recovery system itself through a four-petal configuration that lets the vehicle approach from any direction. The system is construction for ocean floor mounting and first and foremost to be a recharging platform for the Florida Atlantic University’s Ocean Explorer UUV. The system from Woods Hole that is adapted successfully to their Odyssey AUV (Singh, et al., 2001) has on the other hand a nose mounted scissor shaped latch body that captures a vertical pole mounted between a buoy and a dead weight. 54 Figure 36 – Florida Atlantic University's Ocean Explorer stinger recovery system 6.3.3 Universal Launch and Recovery Module This is a concept formulated by General Dynamics Electric Boat which are, at the time of this investigation, updating the US Navy’s Ohio class submarines into modern SSGNs, Ship Submersibles with Guided Missiles and Nuclear Powered, carrying Tomahawk missiles. The Universal Launch and Recovery Module works as an air lock allowing sailors to put a vehicle into the chamber flood it and eject the vehicle out to sea. When retrieving the UUV the robotic arm would extend grab the vehicle and pull it back on board. Electric Boat prime objective with the system is to let the submarine deploy and recover vehicle that are too large to fit in a normal torpedo tube. The Vertical Launch System is roughly 2.5 meters in diameter while a torpedo tube restricts larger vehicles than 0.53 meter in diameter. There is no information how the UUV homes in on the recovery system, most likely USBL navigation though, nor how the vehicle actually attach itself to the system. A theory, from the author, is that the vehicle could use something similar to the belly mounted stinger, or a arrestor hook a fighter jet have attached to their empennage for achieving the deceleration needed for landing on aircraft carriers. 55 Figure 37 – Illustration of a missile tube recovery system Image courtesy of Andrew Lightner, GE Electric Boat 6.3.4 Sea Owl SUBROV The Sea Owl SUBROV is a recovery system intended to be used from a submarine torpedo tube. Except for being able to recover an UUV the system can also be used for inspection, underwater works, Mine Counter Measures and as a platform for Communications/Surveillance. The recovery works in that way that the SUBROV, which is controlled by a human operator, moves and aligns itself with the incoming UUV. It then uses its gripping tool to dock with the UUV and subsequently steers the vehicle into a torpedo tube for recovery, se Figure 38. The advantage with the system is that it can be incorporated onto any submarine without prior modifications. The negative aspects is of course the system needs human interaction and also that it, to the knowledge of the author, has yet to be tried on a real submarine. SAAB Underwater Systems is presently using a mock up on the bottom of Lake Vättern in Sweden to conduct their trials and demonstration of the system. 56 Figure 38 – Illustration of the SAAB Sea Owl SUBROV system Copyright© SAAB Underwater Systems 6.3.5 Boeing Torpedo mounted retractable arm The torpedo mounted retractable arm from Boeing Advanced Information Systems is just as it sounds like an arm that takes hold of a UUV and pulls it into an neighbouring torpedo tube. In figure 39 a drawing of the system is shown. The recovery system is part of Boeings Long-term Mine Reconnaissance System (LMRS), known as AN/BLQ-11, and is capable of launch and recoveries at speed from the US Navy SSN 688 and NSSN class submarines. The system was tested successfully in 2007 on the USS Hartford attack submarine but not without difficulties. The UUV needs to line up directly with the torpedo tube so that the robotic arm can reach out and grab it. The advantage of the system is of course that it is works. Negatively, the system is very expensive, heavy (2 000 kg) and that it use a torpedo tube. In addition, the system could probably not be fitted on a Collins class submarine due to the different positioning of the torpedo tubes compared to the US navy submarines8. 8 The Collins class have their torpedo tubes situated in the front on a horizontal row while the US Navy submarines have their coming out on the side. 57 Figure 39 – Schematic overview of a torpedo mounted arm recovery system9, where: 1 is the Torpedo tube which the system is installed in, 2 is the torpedo tube which the UUV get recovered to, 3 is the outer hull of the Submarine, 4 is an extendable cylindrical arm, 5 is the unfolding gripping tool and 6 is the UUV. Provided by PatentStorm, (PatentStorm). 6.3.6 Reverse Funnel Recovery – Authors suggestion The author suggests a recovery system which offers a way around the control issues with the torpedo shaped vehicle. In this case the LARS system looks similar to a funnel but has its opening towards the front of the submarine. The UUV should in its recovery mode position itself next to the submarine and in front of the funnel opening. After which either the submarine could increase/or the UUV decrease its speed so that the smaller vehicle would slide into the funnel with its aft first. By being in front of the recovery system the UUV is not to experience any of the problems related to a turbulent wake. To navigate the UUV to the designated position a triangulation with i.e. USBL would be used. 9 This system was patented by Lockheed Martin and it is not known whether BOEING a similar or the same system. 58 7 Conclusion Position 1 would be at first glance a good choice for an engineer to conduct a recovery with an UUV. There is no disturbance in terms of large trailing wakes after a sail. There will probably be minor turbulence and wakes due to sonar arrays, openings and irregularities in the hull. There are though other issues with recovering a UUV at this position. There are and probably will be control surfaces around the sail and a few antennas etc. that could get damaged if the recovery procedure of some reason would fail. The greatest force extracted from the simulations was from position 2 and is a spike force in the order of roughly 75 Newton. Except from that case the forces at the rest of the positions are in the size of 10-30 Newton, which shouldn’t create a problem for an UUV. But as explained earlier these forces represents an average over an unknown time which gives no knowledge how fast they are fluctuating or the size of the magnitudes. Problem could arise in this specific case with the REMUS 600 UUV which has its rudders in front of its propeller thus a relatively long rudder response time. If the turbulent fluid changes direction fast enough to push the UUV repeatedly out of its trajectory it would have no way of counteract this with its limited control ability. The same reasoning applies for all the torpedo shaped UUVs presented above. Two of the Launch and Recovery System available on the market sounds promising. Neither the Universal Launch and Recovery Module nore the Belly mounted Stinger cause vorticity in the area of approach for the UUV. Finally, even though a torpedo shaped UUV lacks in control the author believes that its endurance abilities make it the best solution at this stage. However the recovery system needs to be constructed and placed so that the UUV is minimally exposed of turbulent fluid. 59 8 Further work Suggestively a person who continues this work should start with accessing more detailed information about performance data for the different UUVs. If a supplier of an “odd”-shaped UUV can present data showing that an “odd”-shaped UUV can operate for 24 hours, and still have enough power to return to its mother vessel and perform a safe recovery, then this type would have the advantage. Furthermore more work on virtual tether systems and USBL triangulations should be conducted so it can be determined whether a UUV is to have sufficient control and position accuracy to manoeuvre itself close to its host. In the CFD part more time should be spent on the grid around the UUVs control surfaces, or omitting them completely, and successfully conducting a transient simulation. Also providing that a new version of CD-Adapco Star CCM+ supports a six degree of freedom simulation and or an overset grid approach such simulation should be attempted. However the easiest way of determine whether a UUV could be controlled in turbulence would be to conduct real life experiments. 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