報告承辦單位:數(shù)學(xué)與統(tǒng)計學(xué)院
報告內(nèi)容: A flux-jump preserved gradient recovery technique and its application in predicting the electrostatic field
報告人姓名: 應(yīng)金勇
報告人所在單位: 中南大學(xué)數(shù)學(xué)與統(tǒng)計學(xué)院
報告人職稱/職務(wù)及學(xué)術(shù)頭銜:講師/碩導(dǎo)
報告時間: 2019年4月12日，11:00—12:00
報告地點: 金盆嶺1A－406
報告人簡介:應(yīng)金勇，男，博士，碩士生導(dǎo)師。2016年獲美國威斯康辛大學(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)值計算，目前主持國家自然科學(xué)基金一項，湖南省自然科學(xué)基金一項，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.
