activity
20202023
most citedKinetics Parameter Optimization via Neural Ordinary Differential Equations

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2023

A dynamic combustion model for supersonic turbulent combustion

Xu Zhu, Jian An, Nana Wang +2

Supersonic combustion plays a vital role in various applications, including scramjets, dual-mode ramjets, and pulse detonation engines. However, the flame characteristics can vary…

physics.flu-dyn2023

An investigation of subgrid mixing timescale modelling in LES of supersonic turbulent flames

Jian An, Jieli Wei, Jian Zhanga +2

The predictive numerical simulation of supersonic turbulent combustion, in which the turbulent intensity is high and the fuel/air mixture is near the flammability limit, remains ch…

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…