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预告:应金勇: A flux-jump preserved gradient recovery technique and its application in predicting the electrostatic field

发布日期:2019年04月11日 来源:数学与统计学院

报告承办单位:数学与统计学院

报告内容:A flux-jump preserved gradient recovery technique and its application in predicting the electrostatic field

报告人姓名:应金勇

报告人所在单位: 中南大学数学与统计学院

报告人职称/职务及学术头衔:讲师/硕导

报告时间: 201941211:00—12:00

报告地点: 金盆岭1A-406

报告人简介:应金勇,男,博士,硕士生导师。2016年获美国威斯康辛大学密尔沃基分校理学博士学位。主要从事生物数学系统的数值计算,目前主持国家自然科学基金一项,湖南省自然科学基金一项,已经在Journal of Computational Physics, Journal of Computational and Applied Mathematics, Physical Review E等SCI期刊发表论文十多篇。

报告摘要:Poisson-Boltzmann equation (PBE) and its variants are important implicit continuum models for predicting the electrostatics of solvated biomolecules. In this paper, in order to accurately predict the gradient of electrostatics, we propose a new flux-jump preserved gradient recovery method and then fulfill it in the program using Python and Fortran. Numerical tests are used to show our new method is working well.

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