3 citations · 6 across the 16 of their papers we have counts for
4 papers · 1 filter
A comprehensive study on the accuracy and generalization of deep learning-generated chemical ODE integrators
Han Li, Ruixin Yang, Min Zhang +2
The application of deep neural networks (DNNs) holds considerable promise as a substitute for the direct integration of chemical source terms in combustion simulations. However, ch…
An integrated framework for accelerating reactive flow simulation using GPU and machine learning models
Runze Mao, Yingrui Wang, Min Zhang +5
Recent progress in artificial intelligence (AI) and high-performance computing (HPC) have brought potentially game-changing opportunities in accelerating reactive flow simulations.…
GPU-accelerated Large Eddy Simulation of turbulent stratified flames with machine learning chemistry
Min Zhang, Runze Mao, Han Li +2
Stratified premixed combustion, known for its capability to expand flammability limits and reduce overall-lean combustion instability, has been widely adopted to comply with increa…
Detailed simulation of LOX/GCH4 flame-vortex interaction in supercritical Taylor-Green flows with machine learning
Jiayang Xu, Yifan Xu, Zifeng Weng +4
Accurate and affordable simulation of supercritical reacting flow is of practical importance for developing advanced engine systems for liquid rockets, heavy-duty powertrains, and…