140 citations · 150 across the 4 of their papers we have counts for
11 papers
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…
Operator learning for predicting multiscale bubble growth dynamics
Chensen Lin, Zhen Li, Lu Lu +3
Simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investiga…
Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows
Lifei Zhao, Zhen Li, Zhicheng Wang +3
Active- and transfer-learning are applied to polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The resul…
Controlled release of entrapped nanoparticles from thermoresponsive hydrogels with tunable network characteristics
Yi Wang, Zhen Li, Jie Ouyang +1
Thermoresponsive hydrogels have been studied intensively for creating smart drug carriers and controlled drug delivery. Understanding the drug release kinetics and corresponding tr…
Mesoscopic modeling of heptane: A surface tension calculation
Qi Rao, Yidong Xia, Jiaoyan Li +3
Accurate and efficient flow models for hydrocarbons are important in the development of enhanced geotechnical engineering for energy source recovery and carbon capture & storage in…
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…