3 citations · 3 across the 2 of their papers we have counts for
5 papers
Graphics Processing Unit/Artificial Neural Network-accelerated large-eddy simulation of turbulent combustion: Application to swirling premixed flames
Min Zhang, Runze Mao, Han Li +2
Within the scope of reacting flow simulations, the real-time direct integration (DI) of stiff ordinary differential equations (ODE) for the computation of chemical kinetics stands…
Large-eddy simulation of turbulent spray flames: Effects of scalar correlation and enthalpy reduction in flamelet modeling
Dong Wang, Min Zhang, Ruixin Yang +1
Numerical modeling of turbulent spray combustion provides a promising tool for advanced engine design. In spray flames, the droplet evaporation not only reduces the ambient gas tem…
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…