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Machine Learning (ML) has the potential to revolutionise the field of automotive aerodynamics, enabling split-second flow predictions early in the design process.
A single formula for the “law of the wall”
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A tensorial approach to computational continuum mechanics using object-oriented techniques
H G Weller and G Tabor · 1998
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Strategies for turbulence modelling and simulations
Philippe R Spalart · 2000
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The Audi Aeroacoustic Wind Tunnel: Final Design and First Operational Experience
Gerhard Wickern and Norbert Lindener · 2000
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Detached-eddy simulations past a circular cylinder
A Travin, M Shur, M Strelets, and P R Spalart · 2000
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Adaption of eddy-viscosity turbulence models to unsteady separated flow behind vehicles
F. R. Menter and M Kuntz · 2003
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Aerodynamics of Race Cars
Joseph Katz · 2006
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A New Version of Detached-Eddy Simulation, Resistant to Ambiguous Grid Densities
P. R. Spalart, S. Deck, M. L. Shur, K. D. Squires, M. Kh. Strelets, and A. Travin · 2006
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A New Version of Detached-eddy Simulation, Resistant to Ambiguous Grid Densities
P. R. Spalart, S. Deck, M. L. Shur, K. D. Squires, M. Kh. Strelets, and A. Travin · 2006
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Partial Differential Equations
L.C. Evans · 2010
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Detection of initial transient and estimation of statistical error in time-resolved turbulent flow data
C. Mockett, T. Knacke, and F. Thiele · 2010
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Detection of initial transient and estimation of statistical error in time-resolved turbulent flow data
C. Mockett, T. Knacke, and F. Thiele · 2010
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Using singular values to build a subgrid-scale model for large eddy simulations
Franck Nicoud, Hubert Baya Toda, Olivier Cabrit, Sanjeeb Bose, and Jungil Lee · 2011
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Using singular values to build a subgrid-scale model for large eddy simulations
Franck Nicoud, Hubert Baya Toda, Olivier Cabrit, Sanjeeb Bose, and Jungil Lee · 2011
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Experimental and numerical investigation of the drivaer model
Angelina I Heft and Nikolaus A Adams · 2012
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Introduction of a New Realistic Generic Car Model for Aerodynamic Investigations
Angelina I. Heft, Thomas Indinger, and Nikolaus A. Adams · 2012
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Introduction of a New Realistic Generic Car Model for Aerodynamic Investigations
Angelina I. Heft, Thomas Indinger, and Nikolaus A. Adams · 2012
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Potential effects of Rhie & Chow type interpolations in airframe noise simulations
T. Knacke · 2013
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A novel DES-based approach to improve transition from RANS to LES in free shear layers
M. Fuchs, C. Mockett, M. Steger, and F. Thiele · 2014
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Numerical Simulations of Flow around a Realistic Generic Car Model
Emmanuel Guilmineau · 2014
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Go4Hybrid: A European Initiative for Improved Hybrid RANS-LES Modelling
C Mockett, W Haase, and F Thiele · 2014
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Experimental Comparison of the Aerodynamic Behavior of Fastback and Notchback DrivAer Models
Dirk Wieser, Hanns-Joachim Schmidt, Stefan Müller, Christoph Strangfeld, Christian Nayeri, and Christian Paschereit · 2014
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Comparison of RANS and DES Methods for the DrivAer Automotive Body
Neil Ashton and Alistair Revell · 2015
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Assessment of novel DES approach with enhanced SGS modelling for prediction of separated flow over a delta wing
M. Fuchs, C. Mockett, J. Sesterhenn, and F. Thiele · 2015
Cited alongside, same era.
Two non-zonal approaches to accelerate RANS to LES transition of free shear layers in DES
C. Mockett, M. Fuchs, A. Garbaruk, M. Shur, P. Spalart, M. Strelets, F. Thiele, and A. Travin · 2015
Cited alongside, same era.
Simulating DrivAer with Structured Finite Difference Overset Grids
Brett C Peters, Mesbah Uddin, Jeremy Bain, U N C Charlotte, and Motorsports Engineering · 2015
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Two non-zonal approaches to accelerate RANS to LES transition of free shear layers in DES
C. Mockett, M. Fuchs, A. Garbaruk, M. Shur, P. Spalart, M. Strelets, F. Thiele, and A. Travin · 2015
Cited alongside, same era.
Towards an enhanced protection of attached boundary layers in hybrid RANS/LES methods
Sébastien Deck and Nicolas Renard · 2020
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The grey-area improved σ \sigma -DDES approach: Formulation review and application to complex test cases
M. Fuchs, C. Mockett, J. Sesterhenn, and F. Thiele · 2020
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Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta, Xiongye Xiao, and Paul Bogdan · 2021
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On the Aerodynamics of the Notchback Open Cooling DrivAer: A Detailed Investigation of Wind Tunnel Data for Improved Correlation and Reference
Burkhard Hupertz, Karel Chalupa, Lothar Krueger, Kevin Howard, Hans-Dieter Glueck, Neil Lewington, Jin-Hyuck Chang, and Yong-su Shin · 2021
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Fourier Neural Operator for Parametric Partial Differential Equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar · 2021
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An Enhanced Version of des with Rapid Transition from RANS to les in Separated Flows
Mikhail L. Shur, Philippe R. Spalart, Mikhail Kh Strelets, and Andrey K. Travin · 2015
Cited alongside, same era.
Assessment of RANS and DES methods for realistic automotive models
N. Ashton, A. West, S. Lardeau, and A. Revell · 2016
Cited alongside, same era.
A Numerical and Experimental Evaluation of Open Jet Wind Tunnel Interferences using the DrivAer Reference Model
Christopher Collin, Steffen Mack, Thomas Indinger, and Joerg Mueller · 2016
Cited alongside, same era.
Eddy-Resolving Simulations of the Notchback ‘ DrivAer ’ Model : Influence of Underbody Geometry and Wheels Rotation on Aerodynamic Behaviour
Suad Jakirlic, Lukas Kutej, Daniel Hanssmann, and Cameron Tropea · 2016
Cited alongside, same era.
Large eddy simulation with modeled wall-stress: recent progress and future directions
Johan Larsson, Soshi Kawai, Julien Bodart, and Ivan Bermejo-Moreno · 2016
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Assessment of different meshing strategies for low Mach number noise prediction of a rudimentary landing gear
M. Fuchs, Fischer D., C. Mockett, F. Kramer, T. Knacke, J. Sesterhenn, and F. Thiele · 2017
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Critical Assessment of Some Popular Scale-Resolving Turbulence Models for Vehicle Aerodynamics
Suad Jakirlic, Lukas Kutej, Peter Unterlechner, and Cameron Tropea · 2017
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Physics-informed neural operator for learning partial differential equations
Zongyi Li, Hongkai Zheng, Nikola Kovachki, David Jin, Haoxuan Chen, Burigede Liu, Kamyar Azizzadenesheli, and Anima Anandkumar · 2021
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Learning mesh-based simulation with graph networks
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On the Aerodynamics of the Notchback Open Cooling DrivAer: A Detailed Investigation of Wind Tunnel Data for Improved Correlation and Reference
Burkhard Hupertz, Karel Chalupa, Lothar Krueger, Kevin Howard, Hans-Dieter Glueck, Neil Lewington, Jin-Hyuck Chang, and Yong-su Shin · 2021
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HLPW-4/GMGW-3: Hybrid RANS/LES Technology Focus Group Workshop Summary
N Ashton, P Batten, A Cary, and K Holst · 2022
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Overview and Summary of the First Automotive CFD Prediction Workshop: DrivAer Model
Neil Ashton and William Van Noordt · 2022
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Message passing neural pde solvers
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Meire Fortunato, Tobias Pfaff, Peter Wirnsberger, Alexander Pritzel, and Peter Battaglia · 2022
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Two computational studies of a flatback airfoil using non-zonal and embedded scale-resolving turbulence modelling approaches
M. Fuchs, P. Weihing, T. Kuehn, M. Herr, A. Suryadi, C. Mockett, H. Knobbe-Eschen, F. Kramer, and T. Knacke · 2022
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Towards a Standardized Assessment of Automotive Aerodynamic CFD Prediction Capability - AutoCFD 2: Ford DrivAer Test Case Summary
Burkhard Hupertz, Neil Lewington, Charles Mockett, Neil Ashton, and Lian Duan · 2022
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Deep Learning for Real-Time Aerodynamic Evaluations of Arbitrary Vehicle Shapes
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer, and Harald Köstler · 2022
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A statistical approach for optimising HPC costs in high-fidelity CFD simulations
C. Mockett, T. Knacke, N. Schönwald, and R. Cecora · 2022
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Towards a Standardized Assessment of Automotive Aerodynamic CFD Prediction Capability - AutoCFD 2: Windsor Body Test Case Summary
Gary J. Page and Astrid Walle · 2022
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MultiScale MeshGraphNets
Meire Fortunato, Tobias Pfaff, Peter Wirnsberger, Alexander Pritzel, and Peter Battaglia · 2022
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Towards a Standardized Assessment of Automotive Aerodynamic CFD Prediction Capability - AutoCFD 2: Ford DrivAer Test Case Summary
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Pad correction estimation around 5 belt wind tunnel wheel belts using pressure tap measurement and mathematical pressure distribution model
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Gnn-based physics solver for time-independent pdes
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Learning skillful medium-range global weather forecasting
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Geometry-Informed Neural Operator for Large-Scale 3D PDEs
Zongyi Li, Nikola Borislavov Kovachki, Chris Choy, Boyi Li, Jean Kossaifi, Shourya Prakash Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, and Anima Anandkumar · 2023
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Current and emerging deep-learning methods for the simulation of fluid dynamics
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Machine Learning for Road Vehicle Aerodynamics
Vidyasagar Ananthan, Neil Ashton, Nate Chadwick, Mariano Lizarraga, Danielle C Maddix, Satheesh Maheswaran, Pablo Hermoso Moreno, Parisa M Shabestari, Sandeep Sovani, Shreyas Subramanian, Srinivas Tadepalli, and Peter Yu · 2024
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