A Domain Decomposition Method for Strongly Mixed Boundary Value Problems for the Poisson Equation

Dang Quang A () and Vu Vinh Quang ()
Additional contact information
Dang Quang A: Institute of Information Technology
Vu Vinh Quang: Thai Nguyen University, Faculty of Information Technology

A chapter in Modeling, Simulation and Optimization of Complex Processes, 2012, pp 65-75 from Springer

Abstract: Abstract Recently we proposed a domain decomposition method (DDM) for solving a Dirichlet problem for a second order elliptic equation, where differently from other DDMs, the value of the normal derivative on an interface is updated from iteration to iteration. In this paper we develop a method for solving strongly mixed boundary value problems (BVPs), where boundary conditions are of different type on different sides of a rectangle and the transmission of boundary conditions occurs not only in vertices but also in one or several inner points of a side of the rectangle. Such mixed problems often arise in mechanics and physics. Our method reduces these strongly mixed BVPs to sequences of weakly mixed problems for the Poisson equation in the sense that on each side of the rectangle there is given only one type of boundary condition, which are easily solved by a program package, constructed recently by Vu (see [13]). The detailed investigation of the convergence of the method for a model problem is carried out. After that the method is applied to a problem of semiconductors. The convergence of the method is proved and numerical experiments confirm the efficiency of the method.

Keywords: Domain decomposition method; Poisson equation; strongly mixed boundary conditions (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-25707-0_6

Ordering information: This item can be ordered from
http://www.springer.com/9783642257070

DOI: 10.1007/978-3-642-25707-0_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().