ANSA-TGrid: A Common Platform for Automotive CFD Preprocessing · ANSA-TGrid: A Common Platform for...

ANSA-TGrid: A Common Platform for Automotive CFD Preprocessing

Xingshi Wang, PhD, ANSYS Inc. Mohammad “Peyman” Davoudabadi, PhD, ANSYS Inc.

Overview

Motivation Advantages Use Case I: External Aero Dynamic Simulation Use Case II: Vehicle Thermal Management Simulation

Monday, October 06, 2014 2014 Automotive Simulation World Congress 2

Motivation Conventional vs. Integrated Approach


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.

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.

ANSA-TGrid Interface


Part Manager

ANSA-TGrid Tool Tab

ANSA-TGrid Function List

World Car Courtesy of PTC

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

Unique Merits of ANSA-TGrid Process


Assembly

Subassembly

Component

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


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


AdvWrap Group


AdvWrap Results


Single-Surface and TOPO-Mesh Group

Monday, October 06, 2014 2014 Automotive Simulation World Congress

10

Single-Surface and TOPO-Mesh Results


Local Connect


Surface Mesh Ready for Volume Mesh


Volume Mesh

2014 Automotive Simulation World Congress 14

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, 2014

Simulation Results


Turnaround


Subprocess Man Time (Hour)

CPU Time (Hour)

Part Management 1 N/A

AdvWrap 0.5 3

TOPO-Mesh 16 N/A

Prism Layer Validation

4 4

Connect 6 N/A

Surface Mesh Improvement

2 N/A

Volume Mesh 0.5 1.5

Total 30 8.5

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


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


AdvWrap Group


AdvWrap Results


Single-Surface Group and Results


TOPO-Mesh/Wrap Group


TOPO-Mesh/Wrap Results


Local Connect


Surface Mesh Ready for Volume Mesh


Volume Mesh

2014 Automotive Simulation World Congress 26 10 Fluid cell zones, 30.3M tet., Max. Skewness < 0.96 29 Solid cell zones, 3.05M tet., Max. Skewness < 0.95

Heat exchanger MRF fan zone Fuel tank

Cooling duct for rear brake system Monday, October 06, 2014

Solids

Simulation Results


Shells

Turnaround


Subprocess Man Time (Hour)

CPU Time (Hour)

Part Management 1 N/A

AdvWrap 0.5 4

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 0.5 1.5

Total 12 5.5

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

3

6 Main wrap of UH and UB components WrapAdv.; HX+Fan

1

7 Solids surface mesh Surface-mesh or Wrap

3

8 Connect ANSA-TGrid 3

9 7 Design changes 1

Total 20

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

Subprocesses 2-4 and 5-7, executed in parallel.

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


Mesh Subassemblies

Volume Mesh

Geometry Operations

CAD/PLM Read-in

Part Management for Meshing

Setup Post process Solve Connect Subassemblies

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