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| + | ==Abstract== | ||
| + | In this work we develop a component-based model order reduction (CB-pMOR) procedure for a class of problems in nonlinear mechanics with internal variables. The work is motivated by applications to thermo-hydro-mechanical (THM) systems for radioactive waste disposal. The THM system is coupled, time-dependent, and highly nonlinear; furthermore, the solution to the problem depends on several parameters, which might be related to the geometric configuration (e.g. the number of repositories, their distance or their size) or the material properties of the medium. We investigate the effectiveness of the proposed method in terms of accuracy and computational costs for a two-dimensional THM system in the case of overlapping partitions | ||
| + | |||
| + | == Full Paper == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_755799274pap_193.pdf</pdf> | ||
Latest revision as of 11:09, 2 November 2023
Abstract
In this work we develop a component-based model order reduction (CB-pMOR) procedure for a class of problems in nonlinear mechanics with internal variables. The work is motivated by applications to thermo-hydro-mechanical (THM) systems for radioactive waste disposal. The THM system is coupled, time-dependent, and highly nonlinear; furthermore, the solution to the problem depends on several parameters, which might be related to the geometric configuration (e.g. the number of repositories, their distance or their size) or the material properties of the medium. We investigate the effectiveness of the proposed method in terms of accuracy and computational costs for a two-dimensional THM system in the case of overlapping partitions
Full Paper
Document information
Published on 02/11/23
Submitted on 02/11/23
Volume Machine learning and uncertainty quantification for coupled multi-physics, multi-scale and multi-fidelity modelling., 2023
DOI: 10.23967/c.coupled.2023.009
Licence: CC BY-NC-SA license
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