1 citations · 1 across the 5 of their papers we have counts for
5 papers
A Validated LBM Dataset and Pipeline for Surrogate Modeling of Turbulent 3D Obstructed Channel Flows
Lukas Schröder, Shubham Kavane, Harald Köstler
Evaluating neural operators for 3D turbulent flow requires validated datasets with physical benchmarks. We present a reproducible pipeline generating training data for 3D channel f…
Automated Grammar-based Algebraic Multigrid Design With Evolutionary Algorithms
Dinesh Parthasarathy, Wayne Mitchell, Arjun Gambhir +2
Although multigrid is asymptotically optimal for solving many important partial differential equations, its efficiency relies heavily on the careful selection of the individual alg…
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…
Towards Automated Algebraic Multigrid Preconditioner Design Using Genetic Programming for Large-Scale Laser Beam Welding Simulations
Dinesh Parthasarathy, Tommaso Bevilacqua, Martin Lanser +2
Multigrid methods are asymptotically optimal algorithms ideal for large-scale simulations. But, they require making numerous algorithmic choices that significantly influence their…
Evolving Algebraic Multigrid Methods Using Grammar-Guided Genetic Programming
Dinesh Parthasarathy, Wayne Bradford Mitchell, Harald Köstler
Multigrid methods despite being known to be asymptotically optimal algorithms, depend on the careful selection of their individual components for efficiency. Also, they are mostly…