北京大学力学与工程科学学院学术报告

报告人： 王耀宏

天津大学数学学院

时  间：12月26日（周五）14:00-15:30

地  点： 新奥工学大楼1F-1006

Abstract: This talk presents a parallelized Stochastic Eulerian-Lagrangian Method (SELM) framework designed for fluid-structure interaction(FSI) simulations at the micro-scale. The methodology employs a continuous fluid model to resolve the hydrodynamic environment, while the solid phase is represented in the Lagrangian frame. Coarse-grained approaches are introduced to bridge the gap between atomic details and mesoscopic behavior. A primary focus is placed on the coarse-graining of single-stranded DNA and monomers. We implement and evaluate two strategies: the physics-based Iterative Boltzmann Inversion and data-driven Machine Learning techniques, to accurately capture the structural and energetic properties of these biomolecules. To ensure computational feasibility for large-scale systems, a robust parallelization scheme is integrated into the SELM solver. Finally, this framework is applied to research on DNA synthesis, investigating how the interplay between stochastic hydrodynamic forces and molecular interactions influences the synthesis process. 

报告人简介: 王耀宏，天津大学数学学院副教授。本科毕业于复旦大学，2010年博士毕业于美国佛罗里达州立大学应用与计算数学专业，回国前先后在美国加州大学圣巴巴拉分校和美国宾夕法尼亚大学从事博士后研究，研究领域为应用与计算数学， 侧重于界面追踪、微尺度流固耦合和分子动力学问题的数学模型和计算方法的开发及应用。 以一作或通讯在Journal of Computational Physics, SIAM Journal on Scientific Computing, Journal of Fluid mechanics等国外杂志上发表论文十余篇。

联系人：宋保方 baofang.song@pku.edu.cn