2 citations · 2 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2022★ 2 cited
Kinetics Parameter Optimization via Neural Ordinary Differential Equations
Xingyu Su, Weiqi Ji, Jian An +3
Chemical kinetics mechanisms are essential for understanding, analyzing, and simulating complex combustion phenomena. In this study, a Neural Ordinary Differential Equation (Neural…
physics.flu-dyn2020
A Deep Learning Framework for Hydrogen-fueled Turbulent Combustion Simulation
Jian An, Hanyi Wang, Bing Liu +3
The high cost of high-resolution computational fluid/flame dynamics (CFD) has hindered its application in combustion related design, research and optimization. In this study, we pr…
physics.flu-dyn2020
Artificial neural network based chemical mechanisms for computationally efficient modeling of kerosene combustion
Jian An, Guo Qiang He, Kai Hong Luo +2
To effectively simulate the combustion of hydrocarbon-fueled supersonic engines, such as rocket-based combined cycle (RBCC) engines, a detailed mechanism for chemistry is usually r…