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20182022
most citedUsing Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows

10 citations · 26 across the 7 of their papers we have counts for

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physics.flu-dyn20222 cited

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Non-Premixed Combustion on Non-Uniform Meshes and Demonstration of an Accelerated Simulation Workflow

Mathis Bode

This paper extends the methodology to use physics-informed enhanced super-resolution generative adversarial networks (PIESRGANs) for LES subfilter modeling in turbulent flows with…

physics.flu-dyn20222 cited

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors

Mathis Bode

The accurate prediction of small scales in underresolved flows is still one of the main challenges in predictive simulations of complex configurations. Over the last few years, dat…

physics.flu-dyn2022

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data

Mathis Bode, Michael Gauding, Dominik Goeb +2

Models for finite-rate-chemistry in underresolved flows still pose one of the main challenges for predictive simulations of complex configurations. The problem gets even more chall…

physics.flu-dyn20229 cited

Towards prediction of turbulent flows at high Reynolds numbers using high performance computing data and deep learning

Mathis Bode, Michael Gauding, Jens Henrik Göbbert +3

In this paper, deep learning (DL) methods are evaluated in the context of turbulent flows. Various generative adversarial networks (GANs) are discussed with respect to their suitab…

physics.flu-dyn2019

The Role of Differential Diffusion during Early Flame Kernel Development under Engine Conditions -- Part II: Effect of Flame Structure and Geometry

Tobias Falkenstein, Hongchao Chu, Mathis Bode +2

From experimental spark ignition (SI) engine studies, it is known that the slow-down of early flame kernel development caused by the ()-property of common transporta…

physics.flu-dyn2019

The Role of Differential Diffusion during Early Flame Kernel Development under Engine Conditions -- Part I: Analysis of the Heat-Release-Rate Response

Tobias Falkenstein, Aleksandra Rezchikova, Raymond Langer +3

Although experimental evidence for the correlation between early flame kernel development and cycle-to-cycle variations (CCV) in spark ignition (SI) engines was provided long ago,…