报告人简介：

美国马里兰摩根州立大学教授，博导。主要从事数值分析，流体、弹性和生物力学的计算.侧重多物理和多区域问题的建模与计算. 在SIAM Journal on Numerical Analysis, SIAM Journal on Scientific Computing, Mathematics of Computation, Journal of Biomechanical Engineering, American Society of Mechanical Engineers, Journal of Biomechanics等有影响力的SCI期刊上发表论文40多篇，出版book chapters 2部，做大会或邀请报告共 80多次，MathSciNet及40多种计算数学, 计算物理，计算生物力学杂志评审专家, 组织并主持过学术会议：CBMS conference: Deep Learning and Numerical PDEs (2023).

报告简介：

Thermo-poroelastic models capture the interplay between elastic porous material deformation, fluid flow, and thermal effects under non-isothermal conditions. This talk presents a four-field formulation for the linear thermo-poroelastic model and introduces two novel algorithms. The first focuses on constructing parameter-robust preconditioners for the resulting linear system, proposing two approaches: one reorganizes variables into a 2-by-2 block structure, while the other directly addresses the 4-by-4 coupled operator. Both preconditioners exhibit robustness to parameter variations and mesh refinement. The second algorithm is a decoupled iterative finite element method, for which stability and optimal convergence are rigorously proven. Numerical experiments are provided to validate the effectiveness and efficiency of the proposed methods.