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学术报告
学术报告
法国里昻第一大学Leon Matar Tine副教授系列讲座通知
发布人:系统管理员??威尼斯官方网站:2016-05-20?? 浏览次数:352

应数学系杨畅博士的邀请,法国里昻第一大学Leon Matar Tine副教授将于61日至11日访问我校并带来2场精彩的报告,下面是报告的具体信息。欢迎老师和同学与其讨论交流。

 

题 目1Analysis and numerical simulation for a polymerization type model with coagulation

时 间201663 下午200

地 点:数学系会议室(格物楼503

摘 要In this paper we present an analytical and numerical modeling of a general polymerization process with possible lengthening by coagulation mechanism. The proposed model take into account the 3D spatial diffusion of the monomers for the mass transfer between monomers and polymers. This kind of modeling is often used in metallurgy industry , in population dynamics when one focus Prion disease Recent works on Alzheimer disease modeling refer to that process of polymerization with aggregation in order to describe the ways of oligomerization and fibers forming which are considered as vectors of the diseasee investigate the well-posedness of this general polymerization model and propose an adequate 3D numerical scheme based on a generalization of the anti-dissipative method developed in .

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题 目2A hybrid finite volume method for advection equations and its applications in population dynamics

时 间201663 下午300

地 点:数学系会议室(格物楼503

摘 要We will discuss in this talk a very adapted finite volume numerical scheme for transport type-equation. The scheme is an hybrid one combining an anti-dissipative method with down-winding approach for the flux [2, 1] and an high accurate method as the WENO5 one [4]. The main goal is to construct a scheme able to capture in exact way the numerical solution of transport type-equation without artifact like numerical diffusion or without “stairs” like oscillations and this for any regular or discontinuous initial distribution. This kind of numerical hybrid scheme is very suitable when properties on the long term asymptotic behavior of the solution are of central importance in the modeling what is often the case in context of population dynamics where the final distribution of the considered population and its mass preservation relation are required for prediction.

 

 

 

 

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