Interactive Aerodynamic Design in a Virtual Environment

Transcription

1 Interactive Aerodynamic Design in a Virtual Environment M. Meyer, M. Swoboda, Rolls-Royce Deutschland S. Rogge, P. Amtsfeld, C. Hentschel, D. Bestle, BTU Cottbus HPCN Workshop 2012

2 Overview 1. Motivation 2. Aerodynamic design in a virtual environment 1. The virtual environment 2. User interaction 3. Interactive aerodynamic design 3. Conclusions and outlook

3 Extrapolations in Computational Sciences 1 Extrapolation 1: Realism Extrapolation 2: Multi-Disciplinary Extrapolation 3: User Qualification/Education Extrapolation 4: Solution Quality/Certifiable sol. Extrapolation 5: Solution Sensitivity Extrapolation 6: Design of Experiments Extrapolation 7: Design/Optimization Extrapolation 8: Use of Hardware Extrapolation 9: Evolving Work Environment Extrapolation 10: Instant Computing 1 Löhner: Computational Sciences: The Third Pillar of the Empirical Sciences,

4 Towards real-time CFD 500,000 nodes 40 seconds, 1 GPU Real Time 3D Fluid and Particle Simulation and Rendering (2009) 3E6 nodes 7.5 minutes, 1 GPU Real-Time Haptic Interaction with 3D Fluids (2010)

5 The current 3D aerodynamic design process (Example: High pressure turbine)

6 The current 3D aerodynamic design process Process involves the sequential steps of - geometry creation - meshing - pre-processing - solution - post-processing design loop

7 How will we design in the future?

8 Overview 1. Motivation 2. Aerodynamic design in a virtual environment 1. The virtual environment 2. User interaction 3. Interactive aerodynamic design 3. Conclusions and outlook

9 Project IBO: Interactive Blade Optimisation Goals of the project: - Provide a test-bed for novel IT infrastructure - Investigate alternatives to the classic aerodynamic design process - Move towards real-time CFD simulations

10 The Virtual Environment Two back projected displays, each 2.6 m wide and 1.6 m high Display material is glass Angle between displays is 112 Each display has two projectors (overall 4 projectors) Each projector has a WUXGA resolution (1920 x 1200) Pixelwidth: 1.35 mm Head tracking via infrared sensors Gesture detection using Microsoft Kinect

11 The Process Pipeline Meshing Update model parameter 3D grid 3D Flow field Computational Fluid Dynamics (Turbostream)

12 Model Modification Each blade is represented by a parametric model The parameters can be represented in a graphical way Example: lean of the blade circumferential position of blade sections, represented by spheres (called handles) When moving a handle (either with gestures or with the mouse) the parametric model will be updated and the CFD update process is started

13 Gesture detection The Microsoft Kinect Camera is utilized to track user movements Kinect produces depth maps which are used to detect postures and gestures We us OpenNI in conjunction with PrimeSense middleware NITE to dectect pose and basic gestures (Alternatively the Microsoft Kinect SDK could be used)

14 Control of the virtual camera yaw pitch zoom stop

15 Handle control via Grasp Identify hand and determine whether open or closed: Identify separate regions (labels) on the depth image and count them Segmentation is done by a radius search with the hand position as a center Depth hand pixels with certain radius are stored in a temporary map A connected component algorithm helps to count the labels on that map

16 Turbostream CFD Turbostream is a re-implementation of John Denton s TBLOCK solver Developed by Graham Pullan and Tobias Brandvik, Whittle Laboratory, University of Cambridge T. Brandvik, G. Pullan: An Accelerated 3D Navier- Stokes Solver for Flows in Turbomachines. GT , Proc. of ASME Turbo Expo 2009, T. Brandvik, G. Pullan: SBLOCK: A Framework for Efficient Stencil-Based PDE Solvers on Multicore Platforms. Proc. of CIT D (unsteady) Navier-Stokes solver for flows in turbomachinery: able to run on multiple CPUs or GPUs finite volume method with node storage multi-block mesh topology with arbitrary patch interfaces structured grid in cylindrical polar coordinates convergence acceleration by local timestepping, negative feedback and multigrid compressible, real gas U-RANS with turbulence model (mixing length or Spalart-Allmaras)

17 Sample run times (Tesla M2090) 500,000 nodes 40 seconds, 1 GPU 3E6 nodes 7.5 minutes, 1 GPU 120E6 nodes 3.5 hours per revolution, 16 GPUs

18 IBO in action

19 Conclusions & Outlook Prototype of an interactive environment for aerodynamic design has been demonstrated Current calculation time for flow update: ~ 30 seconds Next steps: Speed up of process using profiling and removal of file I/O Integration of additional blade design parameters Integration of different post processing options Investigation of different user interfaces (speech, tablet,...)

20 Acknowledgements This work is part of the research project VIT III: Virtuelles Triebwerk in cooperation with Rolls-Royce Deutschland. It is supported by funding of the Federal State of Brandenburg and the European Union. Contacts: