research
∙
09/12/2023
Toward Discretization-Consistent Closure Schemes for Large Eddy Simulation Using Reinforcement Learning
We propose a novel method for developing discretization-consistent closu...
share
research
∙
06/22/2023
Towards Exascale CFD Simulations Using the Discontinuous Galerkin Solver FLEXI
Modern high-order discretizations bear considerable potential for the ex...
research
∙
06/21/2022
Deep Reinforcement Learning for Turbulence Modeling in Large Eddy Simulations
Over the last years, supervised learning (SL) has established itself as ...
research
∙
05/13/2022
Deep Reinforcement Learning for Computational Fluid Dynamics on HPC Systems
Reinforcement learning (RL) is highly suitable for devising control stra...
research
∙
03/25/2021
Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows
Standard kernel methods for machine learning usually struggle when deali...
research
∙
10/23/2020
A Perspective on Machine Learning Methods in Turbulence Modelling
This work presents a review of the current state of research in data-dri...
research
∙
10/01/2020
A machine learning framework for LES closure terms
In the present work, we explore the capability of artificial neural netw...
research
∙
08/10/2020
An Efficient Sliding Mesh Interface Method for High-Order Discontinuous Galerkin Schemes
Sliding meshes are a powerful method to treat deformed domains in comput...
research
∙
10/07/2019
