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DeepStSNet: Reconstructing the quantum state-resolved thermochemical nonequilibrium flowfield using deep neural operator learning with scarce data 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 491, 页码: 112344
Authors:  Lv JQ(吕家琦);  Hong QZ(洪启臻);  Wang XY(王小永);  Mao, Zhiping;  Sun QH(孙泉华)
Adobe PDF(5558Kb)  |  Favorite  |  View/Download：74/2  |  Submit date：2023/09/26
Hypersonic  Thermochemical nonequilibrium  State-to-state approach  Deep learning  Multiphysics  Data assimilation  
RelaxNet: A structure-preserving neural network to approximate the Boltzmann collision operator 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 490, 页码: 112317
Authors:  Xiao TB(肖天白);  Frank, Martin
Adobe PDF(5203Kb)  |  Favorite  |  View/Download：41/0  |  Submit date：2023/09/05
Kinetic theory  Computational fluid dynamics  Scientific machine learning  Artificial neural network  
Predicting continuum breakdown with deep neural networks 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 489, 页码: 112278
Authors:  Xiao TB(肖天白);  Schotthoefer, Steffen;  Frank, Martin
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Computational fluid dynamics  Kinetic theory  Boltzmann equation  Multi-scale method  Deep learning  
Combining direct and indirect sparse data for learning generalizable turbulence models 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 489, 页码: 112272
Authors:  Zhang XL(张鑫磊);  Xiao, Heng;  Luo, Xiaodong;  He GW(何国威)
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Ensemble Kalman method  Turbulence modeling  Direct data  Indirect data  
An interface-resolved phase-change model based on velocity decomposition 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 卷号: 475, 页码: 28
Authors:  Lu M(卢敏);  Yang ZX(杨子轩);  He GW(何国威)
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Phase-change model  Velocity decomposition  Multi-phase flow