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20232026
most citedA comprehensive study on the accuracy and generalization of deep learning-generated chemical ODE integrators

3 citations · 5 across the 11 of their papers we have counts for

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physics.flu-dyn2026

A Preliminary Assessment of Coding Agents for CFD Workflows

Ke Xiao, Haoze Zhang, Yangchen Xu +3

We investigate the use of tool-using coding agents to automate end-to-end workflows in the open-source CFD package OpenFOAM. Building on general-purpose coding agent interfaces, we…

physics.flu-dyn2024

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…

physics.flu-dyn20233 cited

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…

physics.flu-dyn2023

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…

physics.flu-dyn2023

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…