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An Efficient Parallel MLPG Method for Poroelastic Models

Luca Bergamaschi1,2, ,Ángeles Martínez2, Giorgio Pini2

Corresponding author. Tel.: 0039 049 8271307. E-mail: berga@dmsa.unipd.it
Dipartimento di Metodi e Modelli Matematici per le Scienze Applicate, Università di Padova. Via Trieste 63, 35127 Padova, Italy

Computer Modeling in Engineering & Sciences 2009, 49(3), 191-216. https://doi.org/10.3970/cmes.2009.049.191

Abstract

A meshless model, based on the Meshless Local Petrov-Galerkin (MLPG) approach, is developed and implemented in parallel for the solution of axi-symmetric poroelastic problems. The parallel code is based on a concurrent construction of the stiffness matrix by the processors and on a parallel preconditioned iterative method of Krylov type for the solution of the resulting linear system. The performance of the code is investigated on a realistic application concerning the prediction of land subsidence above a deep compacting reservoir. The overall code is shown to obtain a very high parallel efficiency (larger than 78% for the solution phase) and it is successfully applied to the solution of a poroelastic problem with a fine discretization which produces a linear system with more than 6 million equations using up to 512 processors on the HPCx supercomputer.

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APA Style
Bergamaschi, L., , , Martínez, Á., Pini, G. (2009). An efficient parallel MLPG method for poroelastic models. Computer Modeling in Engineering & Sciences, 49(3), 191-216. https://doi.org/10.3970/cmes.2009.049.191
Vancouver Style
Bergamaschi L, , Martínez Á, Pini G. An efficient parallel MLPG method for poroelastic models. Comput Model Eng Sci. 2009;49(3):191-216 https://doi.org/10.3970/cmes.2009.049.191
IEEE Style
L. Bergamaschi, , Á. Martínez, and G. Pini, “An Efficient Parallel MLPG Method for Poroelastic Models,” Comput. Model. Eng. Sci., vol. 49, no. 3, pp. 191-216, 2009. https://doi.org/10.3970/cmes.2009.049.191



cc Copyright © 2009 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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