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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

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

28 October 2022
Mathis Bode
    AI4CE
ArXivPDFHTML

Papers citing "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"

3 / 3 papers shown
Title
Applying Physics-Informed Enhanced Super-Resolution Generative
  Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean
  Premixed Gas Turbine Combustors
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors
Mathis Bode
AI4CE
17
4
0
28 Oct 2022
Applying Physics-Informed Enhanced Super-Resolution Generative
  Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame
  Kernel Direct Numerical Simulation Data
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data
Mathis Bode
M. Gauding
Dominik Goeb
Tobias Falkenstein
H. Pitsch
AI4CE
17
17
0
28 Oct 2022
Global field reconstruction from sparse sensors with Voronoi
  tessellation-assisted deep learning
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning
Kai Fukami
R. Maulik
Nesar Ramachandra
K. Fukagata
Kunihiko Taira
39
142
0
03 Jan 2021
1