===affil2:
Department of Computer Science, University of Colorado at Boulder
===firstname:
Rongliang
===firstname4:

===firstname3:

===lastname2:
Cai
===lastname:
Chen
===firstname5:

===affil6:

===lastname3:

===email:
rongliang.chen@colorado.edu
===lastname6:

===affil5:

===otherauths:

===lastname4:

===affil4:

===lastname7:

===affil7:

===firstname7:

===postal:
Department of Computer Science 
University of Colorado at Boulder 
Boulder, Colorado 80309
===firstname6:

===ABSTRACT:
A two-level domain decomposition method is introduced for general shape optimization problems constrained by nonlinear partial differential equations. The problem is discretized with a finite element method on unstructured moving meshes and then solved by a parallel two-level one-shot Lagrange-Newton-Krylov-Schwarz algorithm. Due to the pollution effects of the coarse to fine interpolation, direct extensions of the one-level method to two-level do not work. To fix the pollution problem, a pollution removing coarse to fine interpolation scheme is introduced in this paper. As applications, we consider the shape optimization of a cannula problem and an artery bypass problem in 2D. Numerical experiments show that our algorithm performs well on a supercomputer with over one thousand processors for problems with millions of unknowns.
===affil3:

===lastname5:

===affilother:

===title:
A parallel two-level domain decomposition method based inexact Newton method for shape optimization problems
===firstname2:
Xiao-Chuan