activity
20152022
most citedA model-data asymptotic-preserving neural network method based on micro-macro decomposition for gray radiative transfer equations

13 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

math.NA2022★ 13 cited

A model-data asymptotic-preserving neural network method based on micro-macro decomposition for gray radiative transfer equations

Hongyan Li, Song Jiang, Wenjun Sun +2

We propose a model-data asymptotic-preserving neural network(MD-APNN) method to solve the nonlinear gray radiative transfer equations(GRTEs). The system is challenging to be simula…

nlin.AO2020

A stochastic phase model with reflective boundary and induced beating for the cardiac muscle cells

Guanyu Zhou, Tatsuya Hayashi, Tetsuji Tokihiro

We consider the stochastic phase models for the community effect of cardiac muscle cells. The model is the extension of the stochastic integrate-and-fire model in which we incorpor…

math.NA2019★ 1 cited

Staggered DG method for coupling of the Stokes and Darcy-Forchheimer problems

Lina Zhao, Eric Chung, Eun-Jae Park +1

In this paper we develop a staggered discontinuous Galerkin method for the Stokes and Darcy-Forchheimer problems coupled with the \Red{Beavers-Joseph-Saffman} conditions. The metho…

math.NA2018

Penalty method with Crouzeix-Raviart approximation for the Stokes equations under slip boundary condition

Takahito Kashiwabara, Issei Oikawa, Guanyu Zhou

The Stokes equations subject to non-homogeneous slip boundary conditions are considered in a smooth domain . We propose a finite element scheme bas…

math.NA2015★ 1 cited

Penalty method with P1/P1 finite element approximation for the Stokes equations under slip boundary condition

Takahito Kashiwabara, Issei Oikawa, Guanyu Zhou

We consider the P1/P1 or P1b/P1 finite element approximations to the Stokes equations in a bounded smooth domain subject to the slip boundary condition. A penalty method is applied…