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Case Data Analysis Tool for Powerflow

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Case Data Analysis Tool for Powerflow Case Data Analysis Tool for PowerFLOW Dassault Syst`emes- SIMULIA PowerFLOW R GUILLERMO D´IAZ VAZQUEZ´ Master's Degree Project Stockholm, Sweden June 2019 Case Data Analysis Tool for PowerFLOW Dassault Syst`emes- SIMULIA PowerFLOW R Guillermo D´ıazV´azquez Master's Degree Thesis Project MSc in Aerospace Engineering Academic supervisor and examiner: Evelyn Otero KTH Royal Institute of Technology Department of Aerospace Engineering Stockholm, Sweden, 114 28 URL: https://www.kth.se/en ii Abstract The field of computational fluid dynamics (CFD) is exponentially growing in terms of performance, robustness, and applications. The expansion of CFD also means more users and more simulations, which translates into more human errors and mistakes in the simulation set up. Because the simulation set up should be the correct in order to accurately reproduce the desired phenomenon, such errors must be mitigated in order to increase the reliability and robustness of the simulations. In this project a tool has been developed to tackle this issue, within the CFD software SIMULIA PowerFLOW. The tool extracts and analyzes the data of the cases before simulation, reporting the results to the user for error detection. The present work aims to present the implementation, the application and the benefits of the designed tool. iii Referat Case Data Analysverktyg f¨orPowerFLOW Str¨omningsmekaniska ber¨akningar(CFD) omr˚adetv¨axerexponentiellt med avseende p˚aprestanda, robusthet och till¨ampningar. Expansionen av CFD bidrar ¨aven till fler anv¨andareoch simuleringar, vilket i sin tur leder till fler m¨anskligafel och misstag i upps¨attningenav simuleringar. Eftersom simuler- ingsupps¨attningenbeh¨over vara korrekt f¨oratt ˚aterskapa ¨onskade fenomen, beh¨over s˚adanafel undvikas f¨oratt kunna ¨oka simuleringens tillf¨orlitlighet och robusthet. Med avseende p˚adetta utvecklades ett verktyg i CFD mjuk- varan SIMULIA PowerFLOW. Verktyget extraherar och analyserar inst¨allnin- garna f¨oresimulering och rapporterar resultaten till anv¨andaren f¨orfeldetek- tering. Det h¨ararbetet redog¨orf¨orutvecklingen, till¨ampningenoch f¨ordelarna med framst¨alldaverktyget. iv Acknowledgements Firstly, I would like to thank Evelyn Otero for taking the role as my super- visor and examiner, for the careful follow up of my work, and for the effort placed in increasing the quality of this project by giving me an outstanding feedback. I would also like to express my gratitude to the entire SIMULIA team in Stuttgart for their patience and help. In particular to Monti Indro for welcoming into his team. To Matthieu Plagnard for his support, guid- ance and supervision throughout the whole project. Additionally, to Filippo Boscolo for his technical assistance and continuous cooperation. Finally, I am thankfull for the unconditional support and motivation of my family and my girlfriend, Patricia. v Contents 1 Introduction 1 2 Background 3 2.1 Dassault Syst`emes . .3 2.1.1 Field Office Stuttgart . .4 2.2 SIMULIA PowerFLOW Suite . .5 2.3 PowerFLOW background . .7 2.3.1 Navier-Stokes Equations and Continuum Theory . .7 2.3.2 Lattice Boltzmann Method . .9 2.3.3 Contrast of PowerFLOW and Traditional CFD . 12 3 Tool Implementation 15 3.1 Background and Motivation . 15 3.2 Project Statement . 16 3.3 Methodology . 16 3.3.1 Tool Workflow . 17 3.3.2 Features and Content Generated . 18 3.4 Project Management . 20 4 Results 22 4.1 Python Routines . 22 4.1.1 Routines Common Sections . 22 4.1.2 Routine: CdiCheck.py .................. 23 4.1.3 Routine: CdiComp.py .................. 24 4.2 PowerINSIGHT . 26 4.2.1 File: CaseData AnalysisTool.pins ............ 26 4.3 Tool Evaluation . 26 4.3.1 CDI Check results . 27 4.3.2 CDI Comparison results . 36 5 Discussion 44 vi List of Figures 2.1 "The 3D EXPERIENCE Platform" logo and its brands [12] .4 2.2 SIMULIA PowerFLOW suite [9] . .5 2.3 D3Q19 Model . 11 2.4 Overview of one cycle of the LB algorithm. The dark grey boxes show sub-steps that are necessary for the evolution of the solution. The lighter grey box indicates the optional out- put step. The lighter grey box has macroscopic fields to be written to the hard disk for visualisation or post-processing. [8] 12 2.5 NSM and LBM overview . 13 3.1 Case Data Analysis Tool workflow . 17 3.2 Case Data Analysis Tool PowerINSIGHT tree . 19 4.1 Case Data Analysis Tool Content Tree in PowerINSIGHT . 27 4.2 NAS Overview: EV12 Baseline . 28 4.3 Files in CDI and NOT in storage: EV12 Baseline . 28 4.4 Open Shells: EV12 Baseline . 29 4.5 Case Variables: EV12 Baseline . 29 4.6 Case Method Overview: EV12 Baseline . 30 4.7 VR07 Viewpoint: Ground-ISO EV12 Baseline . 30 4.8 VR08 Viewpoint: Ground-ISO EV12 Baseline . 30 4.9 VR09 Viewpoint: Ground-ISO EV12 Baseline . 30 4.10 Body Viewpoint: Ground-Front EV12 Baseline . 31 4.11 Body Viewpoint: Ground-ISO EV12 Baseline . 31 4.12 Body Viewpoint: Ground-Left EV12 Baseline . 31 4.13 Body Viewpoint: Ground-Top EV12 Baseline . 31 4.14 Engine Viewpoint: Ground-ISO EV12 Baseline . 31 4.15 Suspension Viewpoint: Ground-ISO EV12 Baseline . 31 4.16 Wheels Viewpoint: Ground-ISO EV12 Baseline . 32 4.17 Subsystems Viewpoint: Ground-Top EV12 Baseline . 32 4.18 NAS Overview: EV12 Variant . 32 vii Chapter 0 4.19 Files in CDI and NOT in Storage: EV12 Variant . 33 4.20 Files in Storage and NOT in CDI: EV12 Variant . 33 4.21 Name-Matching Files BUT Different Times: EV12 Variant . 33 4.22 Open Shells: EV12 Variant . 34 4.23 Case Variables: EV12 Variant . 34 4.24 Case Method Overview: EV12 Variant . 35 4.25 VR07 Viewpoint: Ground-ISO EV12 Variant . 35 4.26 VR08 Viewpoint: Ground-ISO EV12 Variant . 35 4.27 VR09 Viewpoint: Ground-ISO EV12 Variant . 35 4.28 VR10 Viewpoint: Ground-ISO EV12 Variant . 35 4.29 Body Viewpoint: Ground-Front EV12 Variant . 36 4.30 Engine Viewpoint: Ground-ISO EV12 Variant . 36 4.31 Suspension Viewpoint: Ground-ISO EV12 Variant . 36 4.32 Wheels Viewpoint: Ground-ISO EV12 Variant . 36 4.33 Parts Analysis Overview . 37 4.34 Parts in Variant and NOT in Baseline . 37 4.35 Different Position Only . 38 4.36 Different Area and Position . 38 4.37 Faces Analysis Overview . 38 4.38 Faces in Variant and NOT in Baseline . 39 4.39 Faces with Different Area . 39 4.40 Case Analysis Overview . 40 4.41 Different Value or Unit Variables . 40 4.42 Percentage Difference . 41 4.43 VR10 Viewpoint: Ground-ISO EV12 Comparison . 41 4.44 VR10 Viewpoint: Ground-Left EV12 Comparison . 41 4.45 VR09 Viewpoint: Ground-Front EV12 Comparison . 42 4.46 VR09 Viewpoint: Ground-ISO EV12 Comparison . 42 4.47 Body Viewpoint: Ground-ISO EV12 Comparison . 42 4.48 Body Viewpoint: Ground-Front EV12 Comparison . 42 4.49 Engine Viewpoint: Ground-ISO EV12 Comparison . 43 4.50 Engine Viewpoint: Ground-Front EV12 Comparison . 43 viii Nomenclature CFD - Computational Fluid Dynamics CAE - Computer Aided Engineering P LM - Product Lifecyle Management CAM - Computer Aided Manufacturing CAD - Computer Aided Design VR - Refinement Regions N-S - Navier-Stokes LBM - Lattice Boltzmann Method P DE - Partial Differential Equation PF - SIMULIA PowerFLOW PI - SIMULIA PowerINSIGHT PV - SIMULIA PowerVIZ OS - Operating System LRF - Local Rotating Frame CDAT - Case Data Analysis Tool CSV - Comma-Separated Values PNG - Portable Network Graphics BB - Bounding Box ix Symbols ∇· - Divergence @ - Partial derivative D Dt - Material Derivative ρ - Density p - Pressure q - Heat flux v - Flow velocity τ 0 - Stress tensor e - Internal energy s - Entropy T - Temperature R - Specific gas constant x Chapter 1 Introduction The automotive industry encompasses a wide range of companies and organi- zations which are involved in the design, analysis and manufacturing of motor vehicles [2]. This industry generates one of the world largest revenue mar- kets. Just the top ten companies accumulated revenue of 1.64 trillion U.S. dollars in 2017 [11], producing more than 97 million vehicles in the same year [5]. The automotive industry is constantly evolving, seeking to fulfill customer needs and requests as well as imposed regulations for fuel efficiency, quality, functionality and cost. Manufacturers must carefully trade-off be- tween those values when designing a product. Time is a very critical factor in the development of a product, and automobiles are not an exception. En- gineers need to understand the design compromises either very early in the process or very quickly in order to reduce costs and time, to deliver the best compelling products. Nowadays, such early feedback can be achieved with computer-aided engineering software due to their current levels of accuracy. In the field of CAD and PLM software, Dassault Syst`emesis a world leader due to its vast portfolio of products as well as their quality, function- ality and performance. Among its brands, SIMULIA focuses in software for virtual testing and realistic simulations of different fields. Within SIMU- LIA, the area of CFD is covered by the software conglomerated under the name of PowerFLOW. It is a unique CFD software, considering it is based on inherently transient Lattice Boltzmann physics, which differs from the conventional Navier-Stokes equations solvers. The ability to simulate tran- sient complex shapes, true rotating geometry, wind tunnel conditions, couple simulations with thermal and aeroacoustic analysis, along with paralleliza- tion for quick turn-around times makes it the preferred CFD software in the automobile industry. Experienced engineers are based in strategically located field offices to provide fluid flow simulation and consulting services. This study was performed in one of the aforementioned offices located in 1 Chapter 1 Stuttgart, Germany. This thesis is determined to provide a deeper knowledge of the physics behind the CFD software PowerFLOW and how to employ it in real-world fluid dynamic problems.
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