31 citations · 41 across the 4 of their papers we have counts for
4 papers
PMRT: A Training Recipe for Fast, 3D High-Resolution Aerodynamic Prediction
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer +1
The aerodynamic optimization of cars requires close collaboration between aerodynamicists and stylists, while slow, expensive simulations remain a bottleneck. Surrogate models have…
A Data-Driven Approach for Predicting Hydrodynamic Forces on Spherical Particles Using Volume Fraction Representations
Alexander Metelkin, Sam Jacob Jacob, Bernhard Vowinckel
Particle-laden flows are simulated at various scales using numerical techniques that range from particle-resolved Direct Numerical Simulations (pr-DNS) for small-scale systems to L…
Benchmarking Convolutional Neural Network and Graph Neural Network based Surrogate Models on a Real-World Car External Aerodynamics Dataset
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer +1
Aerodynamic optimization is crucial for developing eco-friendly, aerodynamic, and stylish cars, which requires close collaboration between aerodynamicists and stylists, a collabora…
Deep Learning for Real-Time Aerodynamic Evaluations of Arbitrary Vehicle Shapes
Sam Jacob Jacob, Markus Mrosek, Carsten Othmer +1
The aerodynamic optimization process of cars requires multiple iterations between aerodynamicists and stylists. Response Surface Modeling and Reduced-Order Modeling are commonly us…