1 st Automotive CFD Prediction Workshop Zhenyu Wang 1 and Lian Duan 2 - - PowerPoint PPT Presentation

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1 st Automotive CFD Prediction Workshop Zhenyu Wang 1 and Lian Duan 2 1: Research Scientist, Simulation Innovation and Modeling Center 2: Associate Professor & Honda Endowed Chair in Transportation Computational resources by 1 Summary of

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Computational resources by

1st Automotive CFD Prediction Workshop

Zhenyu Wang1 and Lian Duan2

1: Research Scientist, Simulation Innovation and Modeling Center 2: Associate Professor & Honda Endowed Chair in Transportation

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Summary of Submission

Ø Case 1: SAE Notchback 20 deg Ø Case 2a: DrivAer Fastback

Medium (Total Cells: 165 M) Code Method Spatial Scheme Temporal Scheme Criteria STAR-CCM+ (v13.02.011) SST-DDES Hybrid bounded central difference 2nd order (ΔtU/L = 1.74x10-4) 10.4 convective flow units (1.74 for time-averaged statistics)

Simulations done with Coarse,

Medium and Fine grids provided by workshop committee

Code Method Spatial Scheme Temporal Scheme Criteria STAR-CCM+ (v13.02.011) URANS (realizable k-e) 2nd-order upwind 2nd order (ΔtU/L = 1.43x10-3) 138 convective flow units (28.4 for time-averaged statistics) STAR-CCM+ (v13.02.011) URANS (k-omega SST) 2nd-order upwind 2nd order (ΔtU/L = 1.43x10-3, 2.86x10-3) 138 convective flow units (28.4 for time-averaged statistics) STAR-CCM+ (v13.02.011) SST-DDES Hybrid bounded central difference 2nd order (ΔtU/L = 2.86x10-3) 104 convective flow units (28.4 for time-averaged statistics) STAR-CCM+ (v13.02.011) SST-IDDES Hybrid bounded central difference 2nd order (ΔtU/L = 2.86x10-3) 104 convective flow units (28.4 for time-averaged statistics) Coarse (Total Cells: 93 M)

Simulations done with Cartesian

trimmer mesh for RANS and DES provided by workshop committee

RANS (Total Cells: 4.1 M) DES (Total Cells: 29.1 M) Medium (Total Cells: 258 M)

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Computational Setup

Inlet: Velocity Outlet: Free Outlet Roof: Symmetry Plane Left Wall: Symmetry Plane Right Wall: Symmetry Plane Floor: No-slip Wall

URANS:

Ø Solver: Star-ccm+ 13.02.011 Ø Inlet freestream velocity: 40m/s Ø Inlet turbulence Intensity: 0.2% Ø Wall Treatment: All y+ wall treatment Ø Time step (dt): 3×10-5s and 6×10-5s Ø Inner iterations: 15 and 10 Ø Turbulence model: SST (Menter) k-omega and k-epsilon realizable Min Wall Y+: 0.06 Max Wall Y+: 127.5

Wall Y+

Model Name: SAE Notchback 20 deg Vehicle Dimension: 840mm (L) x 320mm (W) x 240mm (H) Vehicle Frontal Area: 0.076m2

DES:

Ø Solver: Star-ccm+ 13.02.011 Ø Inlet freestream velocity: 40m/s Ø Inlet turbulence Intensity: 0.2% Ø Wall Treatment: All y+ wall treatment Ø Time step (dt): 6×10-5s Ø Inner iterations: 10 Ø Turbulence model: SST (Menter) k-omega IDDES and DDES Min Wall Y+: 0.09 Max Wall Y+: 83.1

Wall Y+ Computational Domain & Boundary Conditions

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Force Prediction

Drag Coefficient

Zero Yaw Angle Exp. SST URANS (dt = 6e-5 s) SST URANS (dt = 3e-5 s) RKE URANS (dt = 3e-5 s) IDDES_SST DDES_SST Cl

0.035
0.07
0.07
0.075
0.076
0.0785

Cd 0.207 0.194 0.193 0.197 0.226 0.198 Cm

0.075
0.066
0.067
0.065
0.138
0.124

Lift Coefficient

Ø Force prediction of URANS is insensitive to time step Ø Good predictions in Cd for all modeling techniques Ø The origin for moment calculation is at X=-10mm, good predictions in Cm for all URANS Models Ø All models give erroneous predictions of Cl

Moment Coefficient

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Pressure Prediction

Time-Averaged Pressure Coefficient

5 Experiment URANS_SST k-w_dt=6e-5s URANS_SST k-w_dt=3e-5s Time step change has little influence

n prediction of

pressure distribution DDES_ SST k-w_dt=6e-5 IDDES_SST k-w_dt=6e-5s

Ø URANS and DES give similar predictions in Cp Ø Apparently good correlation between URANS/DES and experiment Ø DDES seems to overpredict the strength of trailing pillar vortices

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Pressure Prediction

Time-Averaged Pressure Coefficient at Mid-Plane (Y=0)

Ø Predictions of URANS and DDES correlate well with the experiment Ø Cp predicted by IDDES deviates appreciably from those of other models and the experiment in regions close to the notchback

840mm 240mm 20° 30° X Z

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Z = -60mm

Case 1 – Pressure Prediction

Time-Averaged Pressure Coefficient at the Base Surface (x = 420mm)

Z = -120mm Z = -180mm

Z = -180mm Z = -150mm Z = -120mm Z = -90mm Z = -60mm

Y Z

Ø URANS provides equally well or slightly better predictions than the DDES Ø IDDES shows largest significant deviation from the experiment

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Velocity Prediction

Inspection Locations on the Mid-plane (Y = 0)

X=0mm X=-150mm X=-300mm X=-450mm

X Z

X = 0mm X = -150mm X = -300mm X = -450mm

Ø All the turbulence models have similar results over the roof (x = 0mm) Ø URANS gives similar velocity profiles to DDES at all locations Ø IDDES deviates from the other three models in the backlight/boot- deck/base regions

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Velocity Prediction

Time-Averaged Velocity at Mid-Plane (Y=0 mm)

9 Experiment URANS_SST k-w URANS_ke-realizable

Ø URANS underpredicts flow separation over the backlight surface, while IDDES significantly overpredicts flow separation Ø DDES best predicts the extent

f flow separation

IDDES_SST k-w DDES SST k-w

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Q-Criterion

URANS_SST k-w URANS_ke-realizable IDDES_SST k-w DDES_SST k-w 10

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – RMS of Pressure Coefficient

Experiment URANS_SST k-w URANS ke-realizable IDDES_SST k-w

Ø All models fail to predict values of RMS Cp

Significant underprediction

by URANS

Significant overprediction

by IDDES

DDES model seems to

give the right order of magnitude over the base surface 11 DDES_SST k-w

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 1 – Summary

Ø URANS (URANS_SST & URANS_RKE) and DES (DDES_SST & IDDES_SST) were conducted for the SAE Notchback 20 deg model Ø Timestep insensitivity was achieved for URANS at Δt = 6×10-5 s (ΔtU/L = 2.86x10-3) Ø URANS results are largely insensitivity to turbulence models, although SST k-omega showed slightly more accurate prediction of flow separation over the backlight and bootdeck surfaces Ø URANS and DDES provided good predictions of mean pressure and velocity Ø All models failed to predict values of RMS Cp Ø IDDES significantly overpredicted flow separation over the backlight surface, leading to the large deviation in the prediction of mean pressure and velocity over the backlight, bootdeck, and base surfaces from the experiment Ø DDES performed as the best option in accuracy among all the models, although the RMS of Cp shows significant discrepancy from the experimental data

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a - Computational Domain

Computational Domain & Boundary Conditions

Vehicle Dimension: 4.6 m (L) x 1.778 m (W) x 1.408 m (H) Vehicle Frontal Area: 2.16 m2 13 Model Name: DrivAer Fastback

Inlet: Velocity Outlet: Free Outlet Roof: Symmetry Plane Left Wall: Symmetry Plane Right Wall: Symmetry Plane R

d _ f a r : S t a t i

a r y G r

n d Road_near: Moving Ground

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Numerical Settings

14 Numerical Settings: Ø Solver: Star-ccm+ 13.02.011 Ø Inlet freestream velocity: 16m/s Ø Inlet turbulence Intensity: 0.1% Ø Wall Treatment: All y+ wall treatment Ø Time step: 5×10-5s Ø Inner iterations: 10 Ø Total physical time: 3.0s Ø Turbulence model: DDES-SST Max Wall Y+: 1.54 Coarse (Total Cells: 93M) Max Wall Y+: 1.63 Medium (Total Cells: 165M) HPC Info: Ø Processor: Intel E5-2680 v4 Ø Cores Per Node: 28 Ø Clock speed: 2.4GHZ Ø Memory Per Node: 128GB Ø Cores Used: 840 Ø Total Run Time(s): 298,800 (Medium mesh) Ø Total Iterations: 600,000 (Medium mesh) Ø Time per Iteration Avg:0.498 Medium (Total Cells: 258M) Max Wall Y+: 1.69

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Force Prediction

Mean Lift & Drag Coefficients

15 Cl_total Cl_body (without tires and wheels) Cd_total Cd_body (without tires and wheels) Coarse Mesh (93m) 0.0453 0.0445 0.226 0.185 Medium Mesh (165m)

0.00706
0.00798

0.242 0.190 Fine Mesh (258m)

0.0059

0.002 0.229 0.170

Ø Large differences observed in lift coefficient among coarse, medium, and fine mesh cases Ø Drag coefficient relatively insensitivity to mesh density

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Pressure Distribution

Pressure on Vehicle Surface

16 Coarse_Time-averaged Medium_Time-averaged Coarse_Instantaneous Medium_Instantaneous Fine_Time-averaged Fine_Instantaneous

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Wall Shear Stress Distribution

Instantaneous WSS on the Vehicle Surface

17 Coarse Medium Fine

Compared with the coarse mesh case, small WSS variations can be found between the medium and

fine mesh cases.

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Velocity Distribution

Streamwise Velocity in the Central Plane (Y=0)

18 Coarse_Time-averaged Medium_Time-averaged Coarse_Instantaneous Medium_Instantaneous Fine_Time-averaged Fine_Instantaneous

Larger flow separation region over the backlight surface is observed in the medium and fine mesh

cases.

Higher velocity can be found in the underbody region in the medium and fine mesh cases

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Velocity Distribution

Streamwise Velocity in the Central Plane (Y=0)

19 X=2.0m X=2.5m X=3.0m X=3.5m X=4.0m X=4.5m

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Vorticity Distribution

Vorticity in the Central Plane (Y=0) and Horizontal Plane (Z=0m)

20 Coarse_Time-averaged Medium_Time-averaged Coarse_Instantaneous Medium_Instantaneous Fine_Time-averaged Fine_Instantaneous Medium_Instantaneous Coarse_Instantaneous Fine_Instantaneous

Y=0 Y=0 Z=0

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Isosurface

Iso-surface of Mean Streamwise Velocity < 0

21 Coarse_Mesh Medium_Mesh Fine_Mesh

Q-Criterion

Coarse_Mesh Medium_Mesh Fine_Mesh

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Case 2a – Summary

Ø DDES_SST was conducted using coarse, medium, and fine committee grids for the DrivAer Fastback model Ø Grid convergence study showed that

large differences in lift coefficient among the coarse, medium and fine mesh cases
drag coefficient, surface pressure, and the overall wake structures insensitive to mesh

density

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1st Automotive CFD Prediction Workshop, Dec 11-12, Oxford, UK

Thank you

Technical contact:

Dr. Lian Duan

Department of Mechanical and Aerospace Engineering The Ohio State University Email: duan.322@osu.edu Telephone: 614-292-5078 Fax: 614-292-3163 Mail Address: 2300 West Case Rd, Columbus, OH 43235, USA