Zooming Capabilities of the 1D ESPSS Propulsion Simulation Tool with 3D-CFD Solvers: Implementation and Validation

Similar documents
Calculate a solution using the pressure-based coupled solver.

High-Lift Aerodynamics: STAR-CCM+ Applied to AIAA HiLiftWS1 D. Snyder

Recent & Upcoming Features in STAR-CCM+ for Aerospace Applications Deryl Snyder, Ph.D.

Introduction to C omputational F luid Dynamics. D. Murrin

EXPERIMENTAL VALIDATION OF STAR-CCM+ FOR LIQUID CONTAINER SLOSH DYNAMICS

Computational Study of Laminar Flowfield around a Square Cylinder using Ansys Fluent

Putting the Spin in CFD

STAR SOUTHEAST ASIAN CONFERENCE 2015 June 8-9, 2015 Results within a Reasonable Time Frame. Dr Siauw Wei Long. Co-presenter R.Selvakumar.

COMPUTATIONAL FLUID DYNAMICS ANALYSIS OF ORIFICE PLATE METERING SITUATIONS UNDER ABNORMAL CONFIGURATIONS

A MULTI-DOMAIN ALE ALGORITHM FOR SIMULATING FLOWS INSIDE FREE-PISTON DRIVEN HYPERSONIC TEST FACILITIES

Coupled Simulation of the Fluid Flow and Conjugate Heat Transfer in Press Hardening Processes

Estimation of Flow Field & Drag for Aerofoil Wing

COMPUTATIONAL AND EXPERIMENTAL INTERFEROMETRIC ANALYSIS OF A CONE-CYLINDER-FLARE BODY. Abstract. I. Introduction

STUDY OF FLOW PERFORMANCE OF A GLOBE VALVE AND DESIGN OPTIMISATION

CFD Best Practice Guidelines: A process to understand CFD results and establish Simulation versus Reality

Adjoint Solver Workshop

Introduction to Computational Fluid Dynamics Mech 122 D. Fabris, K. Lynch, D. Rich

Flow and Heat Transfer in a Mixing Elbow

Flow in an Intake Manifold

Computational Fluid Dynamics (CFD) Simulation in Air Duct Channels Using STAR CCM+

Simulation of Convergent Divergent Rocket Nozzle using CFD Analysis

CFD MODELING FOR PNEUMATIC CONVEYING

S-ducts and Nozzles: STAR-CCM+ at the Propulsion Aerodynamics Workshop. Peter Burns, CD-adapco

Numerical and theoretical analysis of shock waves interaction and reflection

NUMERICAL SIMULATIONS OF FLOW THROUGH AN S-DUCT

Axisymmetric Viscous Flow Modeling for Meridional Flow Calculation in Aerodynamic Design of Half-Ducted Blade Rows

Simulation of In-Cylinder Flow Phenomena with ANSYS Piston Grid An Improved Meshing and Simulation Approach

Coupled Analysis of FSI

Missile External Aerodynamics Using Star-CCM+ Star European Conference 03/22-23/2011

Aero-Vibro Acoustics For Wind Noise Application. David Roche and Ashok Khondge ANSYS, Inc.

Virtual Product Development on Venturi Pump

INVESTIGATION OF HYDRAULIC PERFORMANCE OF A FLAP TYPE CHECK VALVE USING CFD AND EXPERIMENTAL TECHNIQUE

Swapnil Nimse Project 1 Challenge #2

First Steps - Ball Valve Design

Speed and Accuracy of CFD: Achieving Both Successfully ANSYS UK S.A.Silvester

Application of Wray-Agarwal Turbulence Model for Accurate Numerical Simulation of Flow Past a Three-Dimensional Wing-body

Tutorial 1. Introduction to Using FLUENT: Fluid Flow and Heat Transfer in a Mixing Elbow

Transition Flow and Aeroacoustic Analysis of NACA0018 Satish Kumar B, Fred Mendonç a, Ghuiyeon Kim, Hogeon Kim

Introduction to Gas Turbine Modelling

CFD Analysis of a Fully Developed Turbulent Flow in a Pipe with a Constriction and an Obstacle

Tutorial 17. Using the Mixture and Eulerian Multiphase Models

Shape optimisation using breakthrough technologies

CFD Topological Optimization of a Car Water-Pump Inlet using TOSCA Fluid and STAR- CCM+

SIMULATION OF PROPELLER-SHIP HULL INTERACTION USING AN INTEGRATED VLM/RANSE SOLVER MODELING.

Thermal Modeling of Small Form Factor

Concept and Performance Simulation with ASTOS

Streamlining Aircraft Icing Simulations. D. Snyder, M. Elmore

MAE 3130: Fluid Mechanics Lecture 5: Fluid Kinematics Spring Dr. Jason Roney Mechanical and Aerospace Engineering

Modeling Evaporating Liquid Spray

Investigation and Feasibility Study of Linux and Windows in the Computational Processing Power of ANSYS Software

Co-Simulation von Flownex und ANSYS CFX am Beispiel einer Verdrängermaschine

Development of an Integrated Computational Simulation Method for Fluid Driven Structure Movement and Acoustics

The Avionics System Test Bench, Functional Engineering Simulator: New Developments in Support of Mission and System Verification

ONE DIMENSIONAL (1D) SIMULATION TOOL: GT-POWER

ITTC Recommended Procedures and Guidelines

CFD-1. Introduction: What is CFD? T. J. Craft. Msc CFD-1. CFD: Computational Fluid Dynamics

Extension and Validation of the CFX Cavitation Model for Sheet and Tip Vortex Cavitation on Hydrofoils

COMPUTATIONAL FLUID DYNAMICS USED IN THE DESIGN OF WATERBLAST TOOLING

Automotive Fluid-Structure Interaction (FSI) Concepts, Solutions and Applications. Laz Foley, ANSYS Inc.

OPTIMISATION OF PIN FIN HEAT SINK USING TAGUCHI METHOD

Cycling Loading Effect on a Solid Propellant Engine Performances Part 2 3D CFD Study and Validation of CFD Results

Ryian Hunter MAE 598

Compressible Flow in a Nozzle

Heat transfer and Transient computations

McNair Scholars Research Journal

Cloud Cavitating Flow around an Axisymmetric Projectile in the shallow water

Use of STAR-CCM+ in Marine and Off-Shore Engineering - Key Features and Future Developments - M. Perić, F. Schäfer, E. Schreck & J.

STAR Global Conference 2012 Noordwijk, March 20-21, The InDesA Virtual Test Bench. Dr. Fabiano Bet Dr. Gerald Seider

Computational Fluid Dynamics Simulation of a Rim Driven Thruster

Appendix P. Multi-Physics Simulation Technology in NX. Christian Ruel (Maya Htt, Canada)

Tutorial: Hydrodynamics of Bubble Column Reactors

Ashwin Shridhar et al. Int. Journal of Engineering Research and Applications ISSN : , Vol. 5, Issue 6, ( Part - 5) June 2015, pp.

Reliability - Based Robust Design Optimization of Centrifugal Pump Impeller for Performance Improvement considering Uncertainties in Design Variable

Pressure Losses Analysis in Air Duct Flow Using Computational Fluid Dynamics (CFD)

Comparison of Classic and Finned Piston Reciprocating Linear Air Compressor Using COMSOL Multiphysics

Modeling Evaporating Liquid Spray

Mesh techniques and uncertainty for modelling impulse jetfans. O. A. (Sam) Alshroof. CFD manager Olsson Fire and Risk

Numerical Simulation of Heat Transfer by Natural Convection in Horizontal Finned Channels

Webinar: TwinMesh for Reliable CFD Analysis of Rotating Positive Displacement Machines

Effect of suction pipe leaning angle and water level on the internal flow of pump sump

Simulation of Flow Development in a Pipe

Optimal design of supersonic nozzle contour for altitude test facility

Design optimization method for Francis turbine

Optimization of under-relaxation factors. and Courant numbers for the simulation of. sloshing in the oil pan of an automobile

Verification of Laminar and Validation of Turbulent Pipe Flows

RAPID LARGE-SCALE CARTESIAN MESHING FOR AERODYNAMIC COMPUTATIONS

Preliminary Spray Cooling Simulations Using a Full-Cone Water Spray

Advances in Simulation for Marine And Offshore Applications. Milovan Perić

Design Verification of Hydraulic Performance. for a Centrifugal Pump using. Computational Fluid Dynamics (CFD)

Introduction to ANSYS SOLVER FLUENT 12-1

Problem description. The FCBI-C element is used in the fluid part of the model.

Optimization of Hydraulic Fluid Parameters in Automotive Torque Converters

NUMERICAL INVESTIGATION OF THE FLOW BEHAVIOR INTO THE INLET GUIDE VANE SYSTEM (IGV)

I. Introduction. Optimization Algorithm Components. Abstract for the 5 th OpenFOAM User Conference 2017, Wiesbaden - Germany

Axial Channel Water Jacket Cooling

Air Assisted Atomization in Spiral Type Nozzles

Rotorcraft Noise Prediction with Multi-disciplinary Coupling Methods. Yi Liu NIA CFD Seminar, April 10, 2012

ON THE NUMERICAL MODELING OF IMPINGING JET HEAT TRANSFER

In-Tunnel CFD Simulation of the HL-CRM in the LaRC 14 x 22 ft. Wind Tunnel Part I: Empty Tunnel Simulation Approaches and Verification Using TAU-DRSM

Introduction to ANSYS CFX

Transcription:

Zooming Capabilities of the 1D ESPSS Propulsion Simulation Tool with 3D-CFD Solvers: Implementation and Validation Kaname Kawatsu and Nobuhiro Yamanishi Japan Aerospace Exploration Agency JAXA's Engineering Digital Innovation Center (JEDI), 2-1-1 Sengen, Tsukuba, Ibaraki 305-8505, Japan e-mail: kawatsu.kaname@jaxa.jp Francesco Di Matteo and Johan Steelant ESTEC-ESA Aerothermodynamics and Propulsion Analysis Section (TEC-MPA), Keplerlaan 1, 2201AZ Noordwijk, Netherlands e-mail: Johan.Steelant@esa.int For the development of propulsion systems such as the liquid rocket engine, the simulation of the whole system at once using high-fidelity models is computationally expensive. Solely improving individual components is not sufficient as the interaction with the full system is essential. Therefore, one is presently forced to optimize a complete system using a low-order model followed by an isolated high-fidelity optimization for particular components. In the present work, construction and feasibility studies of a new methodology, in which low- and high-fidelity models are operated simultaneously, were conducted. Using a framework for coupling the low-order propulsion system simulation tool EcosimPro/ESPSS with a high-fidelity computational fluid dynamics tool, complete systems can be modeled reliably and accurately within a reasonable amount of time. In this paper, feasibility studies of the coupling of low- and high-fidelity tools are demonstrated. 1. INTRODUCTION EcosimPro/ESPSS is a propulsion system analysis tool perfectly suited in the Concurrent Design Facility (CDF) [1] to evaluate the performance of liquid rocket engine systems within a reasonable time frame. This is a necessary requirement for a concept assessment and system trade-off studies. During a CDF session, a consistent set of design parameters can be defined and exchanged throughout the study, and any changes, which may have an impact on other disciplines, should immediately be identified and collectively assessed. In other words, the performance of a liquid rocket engine system should be evaluated adequately in a shorter amount of time. EcosimPro [2] platform is an object-oriented tool capable of modeling various kinds of dynamic systems. This tool has a set of libraries with components models and property functions for the simulation of spacecraft and launcher vehicle propulsion systems, which is called ESPSS [3, 4]. The fidelity of models of ESPSS is based up on empirical formulas, simplified equations and 0D/1D transient equations. The rocket engine system consists of several components such as turbopumps, valves, injectors, and a thrust chamber. These components are connected to each other with pipes and junctions. This system should behave as a pipe-based system, but some components have complex physics such as combustion, cavitation, and mixtures, which require high-fidelity physical modeling for simulation purpose. Performing high-fidelity three-dimensional (3D) computational fluid dynamics (CFD) analyses of the entire engine system and provide a comprehensive explanation of the interactions between the components is one possible approach to evaluate complete engine system s behavior [5]. However, because of the prohibitive cost for development and computation, this approach is difficult to be introduced in particular for a concept assessment or system trade-off study within a shorter turn-around time. EcosimPro is useful for simulating a system s behavior due to its real-time feature and low calculation cost. However, the behavior and performance of some components should be evaluated using a high-fidelity CFD analysis to achieve adequate accuracy. Therefore, a framework for coupling a system analysis tool, EcosimPro, and a high-fidelity numerical simulation was set-up to combine high accuracy and reduced computational cost. To maintain the real-time feature of EcosimPro/ESPSS, the high-fidelity simulation tool should be adapted to only prime components of a rocket engine

system requiring a higher accuracy for system analysis. The interaction with the CFD analysis allows specific components to be modeled more accurately. Furthermore, the CFD simulation can rely on realistic, transient boundary conditions provided by a low-order representation of the surrounding system. By coupling low- and high-fidelity tools, complete technical systems can be modeled reliably and accurately within a reasonable amount of time. A feasibility study demonstrating the coupling between EcosimPro and was conducted for a tank and orifice transient system, which is a simplified model of a propellant supply system consisting of a tank, pipe, and valve. In this framework, EcosimPro was used as a master platform for coupling. A high-fidelity simulation with was limited for demonstration purpose only to an orifice. This work was carried out in collaboration research between ESA/ESTEC and JAXA/JEDI, which is based on Staff Exchange Program between ESA and JAXA. Furthermore, construction and demonstration of the new framework for coupling were supported by ESA/ESTEC. 2. COUPLING LOW- AND HIGH-FIDELITY TOOLS To realize the coupling between low- and high-fidelity tools, several methods can be selected. Improving the accuracy of a whole system analysis may be possible by using a database, which is created from the results of a preliminary high-fidelity simulation that focused on the components of the system. The response surface model (RSM) is a method for creating a database of high-fidelity simulation results. In this technique, the relationship between input parameters and simulation results can be formulated as a function. However, this database may have interpolation errors and the range of the input parameters should be preliminarily predicted to obtain high-fidelity simulation results. Thus, direct coupling was selected in this study. In this direct coupling method, a high-fidelity simulation is conducted during each step of the simulation analysis, which uses a low-fidelity tool. 2-1. EcosimPro/ESPSS EcosimPro is an object-oriented tool capable of modeling various kinds of dynamic systems. EcosimPro has a s et of libraries with component models and property functions for the simulation of spacecraft and launcher vehicle propulsion systems, which is called ESPSS. In this framework for coupling low- and high-fidelity tools, EcosimPro/ESPSS assumes the central role as a main platform, which controls the procedure of the simulation, using C++ library functions. The C++ library function enables the platform to make an interface with the 3D-CFD tools to exchange information between the low- and high-fidelity tools, which realizes the coupling. 2-2. 3D-CFD tool, which was originally developed by the CFD Research Corporation (CFDRC) and is currently owned and distributed by ESI [6], was selected as a 3D-CFD simulation tool for a feasibility study for the coupling of low- and high-fidelity tools. is a multi-physics and multi-disciplinary simulation tool, which has a flexible interface with an outer program using a journaling function in the Python programming language. This journaling function enables control of the simulation process and setup for the simulation conditions by an outer outer program. 2-3. Framework for the coupling Figure 1 shows an overview of the framework for the coupling between the low- and high-fidelity tools. In this framework, an I/O module described in C++ exchanged data between EcosimPro and, and controlled the execution of during the complete system analysis procedure by using a journaling function of, which controlling the setup for boundary conditions. EcosimPro I/O (C++) Figure 1. Overview of framework The whole procedure of the coupling framework was divided into five steps as shown in Fig. 2. These procedures were conducted by using a C++ library based on EcosimPro platform. EcosimPro INIT(EcosimPro) ITER(EcosimPro) T > T_stop yes P U in no P END U in P U in I/O (C++) set_external_model_var get_external_model_var Figure 2. Flowchart of framework

Step1. Initialization and setup of In this framework, the initialization and setup for the 3D-CFD simulation using was conducted by the journaling function. In this procedure, a journal file, which contained all of the required information for the simulation, was created in the Python programming language. Step2. Invoke and execute One of the C++ libraries on the EcosimPro platform, which was named set_external_model_var, controlled an execution command to invoke. High-fidelity simulation using is carried out with setup, which was created in the Python programming language including boundary condition information determined by EcosimPro platform. This high-fidelity simulation will evaluate inlet velocity on orifice part in the case of feasibility study, which was carried out in this work. Step3. Check a result of To determine the next time step value for an EcosimPro side calculation, this framework monitored the s output file, which recorded the inlet velocity at each calculation step using a C++ library, which was named get_external_model_var. If the CFD calculation converged, the inlet velocity value, Uin, was transferred to EcosimPro. Step4. Calculation of Ecosim with new Uin value EcosimPro performed a next time step calculation using the Uin value, which was determined by the high-fidelity CFD simulation using. In this part, system s transient behavior is evaluated by EcosimPro. Step5. Update setup for The inlet pressure drop ( P) calculated by result of transient system analysis using EcosimPro was transferred to to set the new boundary condition of inlet pressure using the C++ library set_external_model_var. This setup is also conducted by the journaling function of. These five steps were controlled automatically by EcosimPro during the whole analysis. Thus, is treated as a component model of EcosimPro. 3. FEASIBILITY STUDY OF FRAMEWORK In this section, detail and results of feasibility study for the new framework are discussed. This feasibility study is carried out to demonstrate a feature of the framework to achieve reliable and accurate numerical modeling of a system within a reasonable amount of time. 3-1. Target A feasibility study demonstrating the coupling between EcosimPro and was conducted for a tank and orifice transient system representing a simplified model of a propellant supply system, which consists of a tank, pipe, and valve, as shown in Fig. 3. Figure 3. Schematic of tank and orifice system In this study, high-fidelity simulations using a 3D-CFD tool were employed only for the orifice component, which was assumed to be a valve of a propellant supply system. The other parts of the system, i.e. tank and pipes, were modeled by EcosimPro. 3-2. Numerical setup for system analysis Figure 4 shows the numerical setup of the tank and orifice system for EcosimPro. This model consists of two tanks and one pipe. The pressure drop ( P) in the orifice pipe depends on the inlet velocity of fluid (U in ). The relationship between P and U in was evaluated using a 3D-CFD tool,, in this coupling framework. Supply Tank Head (H1) = 10 m Tank Area = 0.1 m 2 P = 0.3 MPa Tank#1 Inlet Velocity (U in ) EcosimPro Orifice Pressure drop (DP) Orifice Diameter = 0.04 m Tank#2 Catch Tank Head (H2) = 1 m Tank Area = 1.0 m 2 P = 0.1 MPa Figure 4. Numerical setup for EcosimPro In the procedure of the EcosimPro simulation, the pressure difference between the inlet and outlet of the orifice (HydPipe1) was calculated using the heads of the supply tank and catch tank. The inlet velocity, which was evaluated by, determines a flow rate passing through the orifice pipe. The tank heads at the next time step were calculated using this flow rate. 3-3. Numerical model and condition for 3D-CFD A 3D-CFD simulation was adapted to an orifice component, which is a simplified model for a valve in propellant supply system. When fluid flowed through the orifice, a pressure drop occurred as a result of the resistance to flow. This pressure drop was evaluated by.

Figure 5 shows the computational region and model of the orifice component. This model includes the inlet and outlet pipe of the orifice, which interface with the supply tank and catch tank in the EcosimPro model. 0.6 m 0.4 m Configuration of orifice duct 0.04 m boundary condition of pressure for the analysis was updated using EcosimPro s result to evaluate the inlet velocity at each time step of the unsteady system analysis, which was performed by EcosimPro. Figure 7 shows the time history of the pressure and velocity distributions, which were evaluated by a high-fidelity simulation using. At each time step, the inlet and outlet pressure were fixed as boundary conditions. The distribution of the velocity in the orifice component was adequately predicted from a physical point of view by the high-fidelity simulation. This adequate result of the inlet velocity value was applied to the next time step of the EcosimPro system analysis to evaluate the change in the tank head value. These procedures of coupling between the low- and high-fidelity tools were achieved by the new framework constructed in this study. Topology of grid : All Hexahedra Figure 5. Computational region and model Table 1 s hows the CFD method and condition for the orifice component. The steady state simulation was performed with the inlet pressure, which was determined from EcosimPro s result, to evaluate the inlet velocity of the orifice component. The velocity of the fluid was transferred to the EcosimPro model after the simulation convergence was confirmed by the framework s monitoring function. The monitoring function checked for a difference of the inlet velocity value between the previous and present iteration step. Tank Head (m) 12.0 10.0 8.0 6.0 4.0 2.0 0.0 3.0E+05 0 50 100 150 Time (s) (a) Tank Head Supply Tank Catch Tank 4.8 Solver Module Spatial Differencing Transient Conditions Fluid Inlet BC Outlet BC Wall BC Table 1. CFD method and condition CFD Method Ver.2010 Flow, Turbulence (k-e Standard, Standard Wall) Velocity 2 nd Order, Turbulence 2 nd Order Steady CFD Condition Water Static pressure = From EcosimPro, Static temperature = 293 K Static pressure = 0.100 MPa No-slip 3-4. Results and discussion Figure 6 shows the time history of an EcosimPro output. The tank and orifice system s transient behavior, which was observed as variations of the head, was simulated using EcosimPro. Initially, the head of the supply tank was higher than the head of the catch tank. This difference in head between the supply tank and catch tank decreased with the flow of fluid through the orifice. The flow rate of the fluid was determined by the flow velocity. This velocity was evaluated by a high-fidelity simulation using with a numerical setup by the EcosimPro C++ library at each time step of the EcosimPro analysis. The inlet P (Pa) 2.8E+05 2.6E+05 2.4E+05 2.2E+05 2.0E+05 3.8 0 50 100 150 Time (s) (b) Pressure Drop and Inlet Velocity Figure 6. Time history of EcosimPro output dp u_in 4.6 4.4 4.2 4.0 U in (m/s)

Time (s) t = 0 t = 50 Flow Direction boosters where ESPSS is used for the turbo machinery, etc. - Coupling between EcosimPro/ESPSS and code to evaluate multi-disciplinary aspects such as conjugate heat transfer between rocket engine combustion chambers and cooling channels. t = 100 t = 150 Time (s) t = 0 t = 50 t = 100 t = 150 0.0 Pressure MPa 0.3 (a) Pressure Distributions Flow Direction 0.0 U (m/s) 25.0 (b) Velocity Distributions Figure 7. Time history of output 4. OUTLOOK AND FUTURE APPROACH The numerical procedure performed and described in this paper stimulates for further improvements and developments to increase the reliability and the capabilities of the coupling framework. Next plans envisage covering more complex simulations elaborating the interaction of CFD with the EcosimPro platform: - Coupling between ESPSS and the CFD Tau code for launcher propulsion in general. CFD Tau code is mainly a C FD tool for external hypersonic flow simulation and particular combustion processes such as for scramjets [7]. Application of the coupling could be base-flow LRE nozzle interaction along the trajectory or intakes/nozzles for liquid flying back 5. SUMMARY In this study, a n ew framework to achieve reliable and accurate numerical modeling of a system within a reasonable amount of time was constructed. In this framework, the low-order propulsion system simulation tool EcosimPro/ESPSS was coupled with the high-fidelity CFD tool. EcosimPro functioned as a master platform of the framework for the coupling. The high-fidelity CFD tool simulated only a component part using a numerical setup, which was defined by EcosimPro s result. In addition, the CFD result was used as the condition for the next time step calculation of EcosimPro's transient simulation. The information exchange between EcosimPro and the CFD tool was presented by using a new C++ library of EcosimPro. A feasibility study demonstrating the framework for coupling EcosimPro and was conducted for a tank and orifice system. This system is a simplified model of a propellant supply system, which is constructed of a tank, pipe, and valve. The transient simulation using the framework demonstrated the feasibility of the framework for coupling the low- and high-fidelity tools. ACKNOWLEDGEMENTS The construction and feasibility study of the coupling framework in this study were conducted within the staff exchange program between ESA/ESTEC and JAXA/JEDI, which was supported by Dr. Johan Steelant (TEC-MPA/ESA-ESTEC) and his colleagues. The author greatly appreciates their contributions and support. P: pressure T: temperature U: velocity (Greek letters) : difference (Subscripts) in: inlet NOMENCLATURE REFERENCES [1] ESA/ESTEC web site: http://www.esa.int/esami/cdf/, 2011 [2] EcosimPro. Modeling and Simulation Software. Installation & Getting Started Guide. Version 4.8.

Madrid, EA International, 2010. [3] Empresarios Agrupados, ESPSS EcosimPro Libraries User Manual, 1.4.1 edition, 2009. [4] M. De Rosa, J. Steelant, and J. Moral, ESPSS: European Space Propulsion System Simulation, In Space Conference, May 2008. [5] N. Tani, et al, An End-to-End High Fidelity Numerical Simulation of the LE-X Engine - Engine Performance Evaluation and Risk Mitigation Study -, AIAA-2011-5931, 47th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, San Diego, California, July 31-August 3, 2011. [6], Version 2010. User Guide. Huntsville, AL, ESI-CFD Inc., 2010. [7] Homepage of DLR TAU Code, DLR Institute of Aerodynamics and Flow Technology. : http://tau.dlr.de/, 2012.