663 citations · 1.4k across the 19 of their papers we have counts for
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PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs
Xuhui Meng, Zhen Li, Dongkun Zhang +1
Physics-informed neural networks (PINNs) encode physical conservation laws and prior physical knowledge into the neural networks, ensuring the correct physics is represented accura…
Supervised parallel-in-time algorithm for long-time Lagrangian simulations of stochastic dynamics: Application to hydrodynamics
Ansel L. Blumers, Zhen Li, George Em Karniadakis
Lagrangian particle methods based on detailed atomic and molecular models are powerful computational tools for studying the dynamics of microscale and nanoscale systems. However, t…
A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics
Yidong Xia, Ansel Blumers, Zhen Li +7
Mesoscopic simulations of hydrocarbon flow in source shales are challenging, in part due to the heterogeneous shale pores with sizes ranging from a few nanometers to a few micromet…