報(bào)告承辦單位:數(shù)學(xué)與統(tǒng)計(jì)學(xué)院

報(bào)告內(nèi)容: A flux-jump preserved gradient recovery technique and its application in predicting the electrostatic field

報(bào)告人姓名: 應(yīng)金勇

報(bào)告人所在單位: 中南大學(xué)數(shù)學(xué)與統(tǒng)計(jì)學(xué)院

報(bào)告人職稱/職務(wù)及學(xué)術(shù)頭銜:講師/碩導(dǎo)

報(bào)告時(shí)間: 2019年4月12日，11:00—12:00

報(bào)告地點(diǎn): 金盆嶺1A－406

報(bào)告人簡(jiǎn)介:應(yīng)金勇，男，博士，碩士生導(dǎo)師。2016年獲美國(guó)威斯康辛大學(xué)密爾沃基分校理學(xué)博士學(xué)位。主要從事生物數(shù)學(xué)系統(tǒng)的數(shù)值計(jì)算，目前主持國(guó)家自然科學(xué)基金一項(xiàng)，湖南省自然科學(xué)基金一項(xiàng)，已經(jīng)在Journal of Computational Physics, Journal of Computational and Applied Mathematics, Physical Review E等SCI期刊發(fā)表論文十多篇。

報(bào)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.