13 citations · 19 across the 2 of their papers we have counts for
3 papers
physics.flu-dyn2022★ 13 cited
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model
Jian Li, Dongxiao Zhang, Tianhao He +1
Uncertainty quantification (UQ) of subsurface two-phase flow usually requires numerous executions of forward simulations under varying conditions. In this work, a novel coupled the…
physics.comp-ph2022★ 6 cited
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net
Tianhao He, Haibin Chang, Dongxiao Zhang
Identification of unknown physical processes and parameters of groundwater contaminant sources is a challenging task due to their ill-posed and non-unique nature. Numerous works ha…
physics.geo-ph2020
Deep Learning of Dynamic Subsurface Flow via Theory-guided Generative Adversarial Network
Tianhao He, Dongxiao Zhang
Generative adversarial network (GAN) has been shown to be useful in various applications, such as image recognition, text processing and scientific computing, due its strong abilit…