Parallel implementation of finite element code for twodimensional incompressible Navier-Stokes Equations with scalar transport.

• Ano de defesa: 2010
• Autor(a) principal: López, Pedro Juan Torres
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade do Estado do Rio de Janeiro; Centro de Tecnologia e Ciências::Faculdade de Engenharia; BR; UERJ; Programa de Pós-Graduação em Engenharia Mecânica
• Palavras-chave em Português: Mechanic Engineering; Parallel Finite Element; Static Condensation; Mesh Partition; Large Linear System; PETSc; Engenharia Mecânica; Métodos de Elementos Finitos; Condensação Estática; Particionamento de Malhas; Sistema Linear de Grande; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: http://www.bdtd.uerj.br/handle/1/11709

The study of the water flow and scalar transport in water reservoirs is important for the determination of the water quality during the initial stages of the reservoir filling and during the life of the reservoir. For this scope, a parallel 2D finite element code for solving the incompressible Navier-Stokes equations coupled with scalar transport was implemented using the message-passing programming model, in order to perform simulations of hidropower water reservoirs in a computer cluster environment. The spatial discretization is based on the MINI element that satisfies the Babuska-Brezzi (BB) condition, which provides sufficient conditions for a stable mixed formulation. All the distributed data structures needed in the different stages of the code, such as preprocessing, solving and post processing, were implemented using the PETSc library. The resulting linear systems were solved using the projection method implemented by an approximate block LU factorization. In order to increase the parallel performance in the solution of the linear systems, we employ the static condensation method for solving the intermediate velocity at the vertex and centroid nodes separately. We compare performance results of the static condensation method with the approach of solving the complete system. In our tests the static condensation method shows better performance for large problems, at the cost of an increased memory usage. Performance results for other intensive parts of the code in a computer cluster are also presented.