427 citations · 942 across the 8 of their papers we have counts for
4 papers · 1 filter
A physics-informed variational DeepONet for predicting the crack path in brittle materials
Somdatta Goswami, Minglang Yin, Yue Yu +1
Failure trajectories, identifying the probable failure zones, and damage statistics are some of the key quantities of relevance in brittle fracture applications. High-fidelity nume…
Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural network
Minglang Yin, Ehsan Ban, Bruno V. Rego +4
Aortic dissection progresses via delamination of the medial layer of the wall. Notwithstanding the complexity of this process, insight has been gleaned by studying in vitro and in…
Physics-informed neural networks (PINNs) for fluid mechanics: A review
Shengze Cai, Zhiping Mao, Zhicheng Wang +2
Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier-Stokes equations (NSE), we still cannot incorporate…
Multiscale Parareal Algorithm for Long-Time Mesoscopic Simulations of Microvascular Blood Flow in Zebrafish
Ansel Blumers, Minglang Yin, Hiroyuki Nakajima +3
Various biological processes such as transport of oxygen and nutrients, thrombus formation, vascular angiogenesis and remodeling are related to cellular/subcellular level biologica…