Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2210.16219
Cited By
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors
28 October 2022
Mathis Bode
AI4CE
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors"
2 / 2 papers shown
Title
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
AI4CE
22
3
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
Mathis Bode
M. Gauding
Dominik Goeb
Tobias Falkenstein
H. Pitsch
AI4CE
19
17
0
28 Oct 2022
1