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26.08.21 slide 1
Shape optimizationAnd how foolproof is it?
2nd Automotive CFD Prediction Workshop
Berlin, 26.08.2021
Dr.-Ing. Astrid Walle
Astrid Walle CFDsolutions
26.08.21 slide 2
Background- Mechanical Engineer- PhD in numerical methods- More than a decade in CFD- R&D engineer and Data Scientist at: Siemens, Rolls Royce i.a.
My Specialties:- Optimisation (Surrogate Modeling)- Fluid Structure Interaction (Aeroelastics)- Data Science (Analysis & Visualisation & ML)
Mission and passion: - Bring more Data Science into Engineering- HPC in the cloud
http://www.cfdsolutions.net/
https://www.linkedin.com/in/astridwalle/
https://www.github.com/astridwalle
Demo Application: Windsor Body
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Parameter Space Exploration
Param 1 … Param j Result 1 … Result k 2D Plot 1 … 2D Plot n
Design 1 Int/float Int/float Int/float Int/float filepath filepath
…
Design i
Parameters:front_lengthroof_lengthback_length
Results:Drag CoefficientLift CoefficientPitching Moment Coefficient
front
_len
gth
roof_length
back
_len
gth
https://demo.cfdsolutions.net
Parameter Space Exploration - Results
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https://demo.cfdsolutions.net
- No pins- ~1.3 Mio cells, not the
workshop grid- Varying geometry- Different normalisation,
not directly comparable- RANS, RKE, All y+
Parameter Space Exploration - Results
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Designs:- 1- 23- 63
https://demo.cfdsolutions.net
nW1A: My variations - Drag
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Turbulence Models:- KE (Standard) +63%- RKE (Realizable) 0.27- KW (Wilcox) -18%
All y+ Wall Treatment
Shape Optimization – Turbulence Model
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Shape Optimization – Turbulence Model
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Shape Optimization – Turbulence Model
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26.08.21 slide 10Photo by Franki Chamaki on Unsplash
