3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.DC2025★ 1 cited
Deep Learning-Enabled Supercritical Flame Simulation at Detailed Chemistry and Real-Fluid Accuracy Towards Trillion-Cell Scale
Zhuoqiang Guo, Runze Mao, Lijun Liu +3
For decades, supercritical flame simulations incorporating detailed chemistry and real-fluid transport have been limited to millions of cells, constraining the resolved spatial and…
physics.flu-dyn2023★ 3 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…