English  |  正體中文  |  简体中文  |  Items with full text/Total items : 73032/73032 (100%) Visitors : 23248804      Online Users : 418
 Scope All of NCUIR 理學院    數學研究所       --博碩士論文 Tips: please add "double quotation mark" for query phrases to get precise resultsplease goto advance search for comprehansive author search Adv. Search
 NCU Institutional Repository > 理學院 > 數學研究所 > 博碩士論文 >  Item 987654321/7905

 Please use this identifier to cite or link to this item: `http://ir.lib.ncu.edu.tw/handle/987654321/7905`

 Title: 以平行 Newton-Krylov-Schwarz 演算法解 Poisson-Boltzmann 方程式的有限元素解在膠體科學上的應用;Parallel Newton-Krylov-Schwarz Algorithms for Finite Element Solution of Three Dimensional Poisson-Boltzmann Equations with Applications in Colloidal Science Authors: 蔡尚融;Shang-Rong Cai Contributors: 數學研究所 Keywords: 非精確牛頓法;overlapped Schwarz preconditioning;有限元素法;膠體科學;三維模擬;Poisson-Boltzmann 方程式;Poisson-Boltzmann equation;3D simulation;colloidal science;inexact Newton;overlapped Schwarz preconditioning;finite element method;parallel processing Date: 2008-06-26 Issue Date: 2009-09-22 11:08:41 (UTC+8) Publisher: 國立中央大學圖書館 Abstract: 運用平行的Newton-Krylov-Schwarz 演算法，求大型稀鬆非線性方程式組的解， 此非線性系統是介由有限元素法，作離散化在三維的Poisson-Boltzmann 方程式； 於膠質科學的應用中，做帶電膠質微粒在電解液中的三維數值模擬。Poisson-Boltzmann 方程式， 為描述帶電膠體粒子於電解液中，其電位能分佈情形的方程式。並進行關於平行效能的研究， 討論使用 LU 和 ILU 作為不同的preconditioner 的條件下作比較，其結果顯示， 在使用32 顆處理器時，可達的58 % 效率。 We employ the Newton-Krylov-Schwarz algorithms for solving a large sparse nonlinear system of equations arising from the finite element discretization of three dimensional Poisson-Boltzmann equation (PBE) in the application in colloidal science. The method do the numerical simulation in three dimensional space for the charged colloidal particles in a electrolyte. The PBE is used to describe the distribution of electrostatic potential in a colloidal system. We validate our code by computing the electrostatic forces of their interactions on the charged colloidal particles, and the results agree with other published data. we also conduct parallel performance study on a parallel machine, and the result shows that our code reachs 58% efficiency up to 32 processors. Appears in Collections: [數學研究所] 博碩士論文

Files in This Item:

File SizeFormat