Speaker: Sun Wenjun, researcher at the Institute of Applied Physics and Computational Mathematics and Center for Applied Physics and Technology at Peking University

Date: March 24, 2023

Time: 14:00-15:00

Location: Tencent Meeting

Sponsor: School of Mathematics, Shandong University

Abstract:

This talk aims to introduce 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 simulated with both the traditional numerical schemes and the vanilla physics-informed neural networks(PINNs) due to the multiscale characteristics. Under the framework of PINNs, we employ a micro-macro decomposition technique to construct a new asymptotic-preserving(AP) loss function, which includes the residual of the governing equations in the micro-macro coupled form, the initial and boundary conditions, the additional constraints and a few labeled data. A number of numerical examples are presented to illustrate the efficiency of MD-APNNs, and particularly, the importance of the AP property in the neural networks for the diffusion dominating problems.

For more information, please visit:

https://www.view.sdu.edu.cn/info/1020/176783.htm