Numerical simulation of dynamic discrete systems with domain decomposition and application to granular media

Industrial demand for numerical simulation of granular media is increasing for large systems. The case of interactions between grains such as unilateral contact with friction involves additional difficulties to these simulations. This study investigates a domain decomposition approach. The sub-structuration methods were originally developed for continuous media usually discretized by finite elements for solid mechanics. The LMGC90 platform (software to manage contact with distinct elements) provides a framework for the implementation of algorithms. Thus, domain decomposition algorithms, based on the LArge Time INcrement and Non Linear Gauss Seidel methods, ans suited to a granular problem are defined, implemented and compared. To exploit the potential for parallel computing of the aforementioned methods, the exchanging messages with MPI (Message Passing Interface) is added to the code. Then, the improvement of the scalability of multi-domain approaches through the addition of a macroscopic scale is tested. Finally, in order to implement a dialogue between the discrete (microscopic scale) and continuous (macroscopic scale) models, an enhanced version of the NLGS-DD method (Non Linear Gauss Seidel with domain decomposition) is proposed. The expected acceleration of the convergence is studied theoretically on reduced-size samples, prior to performing some tests on larger samples.

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Source https://theses.hal.science/tel-00800891
Author Iceta, Damien
Maintainer CCSD
Last Updated May 12, 2026, 17:21 (UTC)
Created May 12, 2026, 17:21 (UTC)
Identifier tel-00800891
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Modélisation Mathématique en Mécanique (M3) ; Laboratoire de Mécanique et Génie Civil (LMGC) ; Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)
creator Iceta, Damien
date 2010-07-16T00:00:00
harvest_object_id 751a8a9b-64e7-460a-bc5d-7d7c6ee7aa6b
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2023-03-24T00:00:00
set_spec type:THESE