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Multiscale smoothed particle hydrodynamics model development for simulating preferential flow dynamics in fractured porous media 期刊论文
Water Resources Research, 2020
作者:  E. Shigorina;  F. Rü;  diger;  A. M. Tartakovsky;  M. Sauter;  J. Kordilla
收藏  |  浏览/下载：6/0  |  提交时间：2020/12/22
Method of distributions for quantification of geologic uncertainty in flow simulations 期刊论文
Water Resources Research, 2020
作者:  Hyung Jun Yang;  Francesca Boso;  Hamdi A. Tchelepi;  Daniel M. Tartakovsky
收藏  |  浏览/下载：6/0  |  提交时间：2020/05/25
Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems 期刊论文
WATER RESOURCES RESEARCH, 2020, 56 (5)
作者:  Tartakovsky, A. M.;  Marrero, C. Ortiz;  Perdikaris, Paris;  Tartakovsky, G. D.;  Barajas-Solano, D.
收藏  |  浏览/下载：12/0  |  提交时间：2020/07/02
deep neural networks  physics-informed machine learning  parameter estimation  learning constitutive relationships  unsaturated flow  MAP  
Probabilistic Forecast of Single-Phase Flow in Porous Media With Uncertain Properties 期刊论文
WATER RESOURCES RESEARCH, 2019
作者:  Yang, Hyung Jun;  Boso, Francesca;  Tchelepi, Hamdi A.;  Tartakovsky, Daniel M.
收藏  |  浏览/下载：9/0  |  提交时间：2019/11/27
uncertainty quantification  groundwater flow  random conductivity  method of distributions  risk assessment  rare events  
Uncertainty Quantification in Scale-Dependent Models of Flow in Porous Media 期刊论文
WATER RESOURCES RESEARCH, 2017, 53 (11)
作者:  Tartakovsky, A. M.;  Panzeri, M.;  Tartakovsky, G. D.;  Guadagnini, A.
收藏  |  浏览/下载：3/0  |  提交时间：2019/04/09
flow in porous media  randomness  uncertainty quantification  scale dependence