ANSA-TGrid: A Common Platform for Automotive CFD Preprocessing. Xingshi Wang, PhD, ANSYS Inc. Mohammad Peyman Davoudabadi, PhD, ANSYS Inc.

Transcription

1 ANSA-TGrid: A Common Platform for Automotive CFD Preprocessing Xingshi Wang, PhD, ANSYS Inc. Mohammad Peyman Davoudabadi, PhD, ANSYS Inc.

2 Overview Motivation Advantages Use Case I: External Aero Dynamic Simulation Use Case II: Vehicle Thermal Management Simulation Monday, October 06, Automotive Simulation World Congress 2

3 Motivation Conventional vs. Integrated Approach To create a leakage free, conformal mesh and ensure physical conduction paths, all the overlapping, intersecting, and gap regions have to be fixed and connected. Topo Level: Manual, Time consuming Traditional approach requires users to manually remove gaps, resolve overlaps and intersections for ALL components in the model. In the conventional approach, user has to somehow manually create cap and contact faces to patch leakages and preserve conduction paths. Mesh Level: Semi-automated, More efficient Leverage wrapping technology as much as possible with minimum manual efforts. Wrap surface is leakage free. Invest manual efforts only to create high fidelity surface mesh and preserve conduction path between different materials. Resolve connection on the mesh level is more efficient and flexible. Monday, October 06, Automotive Simulation World Congress 3

4 ANSA-TGrid Interface ANSA-TGrid Tool Tab Part Manager ANSA-TGrid Function List World Car Courtesy of PTC Monday, October 06, Automotive Simulation World Congress 4

5 Unique Merits of ANSA-TGrid Process Highly automated; maximizes the outcome of engineering time Extensive control of mesh quality suitable to all automotive simulations Parallel execution Flexible and heterogeneous inputs (CAD, existing mesh, previous analyses ) From components to assembly Throughout the design cycle Analysis to analysis Mesh tech. to meshing technology Subassembly Assembly Component Monday, October 06, Automotive Simulation World Congress 5

6 Use Case I External Aero Dynamics Simulation Objective Provide accurate prediction for Drag and Lift coefficients. Evaluate design changes for optimization to reduce drag and provide enough down force at the same time. Challenges for CFD Pre-processing Capture features accurately especially on styling surfaces Generate boundary layers to achieve y + ~ 1 on styling surfaces Huge cell counts for typical applications Fast turn around Go through large design changes rapidly Monday, October 06, Automotive Simulation World Congress 6

7 Preprocessing Strategy for External Aero Dynamics Pristine surface mesh on styling surfaces Perfect feature capturing Full control on elements size and quality Fine resolution to resolve boundary layer AdvWrap drive, underhood/underbody and in-cabin components Walk over geometry defects Ensure leakage free surface mesh Preserve important features Reduce engineering time by automation Monday, October 06, Automotive Simulation World Congress 7

8 AdvWrap Group Monday, October 06, Automotive Simulation World Congress 8

9 AdvWrap Results Monday, October 06, Automotive Simulation World Congress 9

10 Single-Surface and TOPO-Mesh Group Monday, October 06, Automotive Simulation World Congress 10

11 Single-Surface and TOPO-Mesh Results Monday, October 06, Automotive Simulation World Congress 11

12 Local Connect Monday, October 06, Automotive Simulation World Congress 12

13 Surface Mesh Ready for Volume Mesh Monday, October 06, Automotive Simulation World Congress 13

14 Volume Mesh Heat exchanger cell zone MRF fan zone 10 Prism layers with Min. height 0.01 mm on all styling surfaces Total cell counts ~ 34.5 M; Max. Skewness < 0.98 Monday, October 06, Automotive Simulation World Congress 14

15 Simulation Results Monday, October 06, Automotive Simulation World Congress 15

16 Turnaround Subprocess Man Time (Hour) Part Management 1 N/A AdvWrap TOPO-Mesh 16 N/A Prism Layer Validation 4 4 Connect 6 N/A Surface Mesh Improvement 2 N/A Volume Mesh Total CPU Time (Hour) Monday, October 06, Automotive Simulation World Congress 16

17 Use Case II Vehicle Thermal Management Simulation Objective Model full vehicle to predict flow and heat transfer through cooling module. Provide accurate temperature prediction for critical components under difference road conditions to improve vehicle quality and reliability. Challenges for CFD Pre-processing Complex and dirty geometry Separate fluid cell zones are required to model secondary fluids/flows Separate solid cell zones are required to obtain accurate temperature prediction in Conjugate Heat Transfer (CHT) simulation Complex case setup Fast turn around Go through large design changes rapidly Monday, October 06, Automotive Simulation World Congress 17

18 Preprocessing Strategy for Vehicle Thermal Management Individual TOPO-Mesh/wrap on components critical to thermal analysis High quality for thermal analysis Ensure leakage free surface mesh Obtain separate cell zones for secondary flows Obtain separate cell zones for different materials Conduction paths persevered by local connect Single-Surface thin solids Leverage shell conduction in FLUENT Reduce cell count and improve mesh quality AdvWrap components not critical to thermal analysis Walk over geometry defects Ensure leakage free surface mesh Preserve important features Reduce engineering time by automation Monday, October 06, Automotive Simulation World Congress 18

19 AdvWrap Group Monday, October 06, Automotive Simulation World Congress 19

20 AdvWrap Results Monday, October 06, Automotive Simulation World Congress 20

21 Single-Surface Group and Results Monday, October 06, Automotive Simulation World Congress 21

22 TOPO-Mesh/Wrap Group Monday, October 06, Automotive Simulation World Congress 22

23 TOPO-Mesh/Wrap Results Monday, October 06, Automotive Simulation World Congress 23

24 Local Connect Monday, October 06, Automotive Simulation World Congress 24

25 Surface Mesh Ready for Volume Mesh Monday, October 06, Automotive Simulation World Congress 25

26 Volume Mesh Heat exchanger Monday, October 06, 2014 MRF fan zone Fuel tank 10 Fluid cell zones, 30.3M tet., Max. Skewness < Solid cell zones, 3.05M tet., Max. Skewness < 0.95 Cooling duct for rear brake system 2014 Automotive Simulation World Congress 26

27 Simulation Results Shells Solids Monday, October 06, Automotive Simulation World Congress 27

28 Turnaround Subprocess Man Time (Hour) Part Management 1 N/A AdvWrap TOPO-Mesh/Wrap 4 N/A Prism Layer Validation 0.5 N/A Connect 5 N/A Surface Mesh Improvement 0.5 N/A Volume Mesh Total CPU Time (Hour) Monday, October 06, Automotive Simulation World Congress 28

29 Typical Industrial Productivity Gains Subprocess Method No. of days 1 Translate CAD to ANSA 2 Upper body including styled surfaces (external aero) Topo-Mesh 5 3 Surface mesh generation (external aero) Topo-Mesh 2 4 Brakes Topo-Mesh 2 5 Part Management (for naming and wrap) Includes fixing large leakages/holes 6 Main wrap of UH and UB components WrapAdv.; HX+Fan 7 Solids surface mesh Surface-mesh or Wrap 8 Connect ANSA-TGrid Full vehicle with all details (~10K components) One common model built for external aero, front-end cooling, brake and thermal simulations CAD to Solution time reduced by 3X with no sacrifice of accuracy Maximizing efficiency across multiple teams 9 7 Design changes 1 Total 20 Subprocesses 2-4 and 5-7, executed in parallel. Monday, October 06, Automotive Simulation World Congress 29

30 Conclusion Semi-automated, streamlined workflow that employs the best of both ANSA and TGrid Increased throughput (w.r.t. man hrs and user comfort); Reusability; Scalability Flexibility and control over mesh quality and accuracy Enables dynamic collaboration and parallel execution PLM/PDM connectivity/portability Allows for higher level of automation And can be readily integrated in the OEMs processes CAD/PLM Read-in Part Management for Meshing Geometry Operations Mesh Subassemblies Post process Solve Setup Volume Mesh Connect Subassemblies Monday, October 06, Automotive Simulation World Congress 30