A computational strategy for poroelastic problems with a time interface between coupled physics

Néron, David; Dureisseix, David

doi:10.1002/nme.2091

Cited by 19 publications

(26 citation statements)

References 34 publications

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“…the stress r for the S-physics or the fluid accumulation q for the F-physics), which are computed only at the integration points. This characteristic implies a slight modification of the technique that was introduced in [5].…”

Section: Dealing With Different Discretizationsmentioning

confidence: 97%

“…A previous article [5] focused on the coupling of time discretizations when performing the simulation of this kind of 2-physics problem. The simplicity and the unidimensionality of the test 1054 D. NÉRON AND D. DUREISSEIX case treated in this article allowed to derive an exact solution, to make some characteristics times appear and to eliminate the spatial aspect in order to focus the presentation on the time coupling aspect.…”

Section: Simulation Of Coupled Multiphysics Problemsmentioning

confidence: 99%

“…To design the time transfer operators, we wish to reuse the same tools; therefore, we have to deal with a time discretization that allows jumps from a time slab to the other and that provides a variational framework. As detailed in [5], the time discontinuous Galerkin (TDG) approach (see [23,24]) is such a candidate; it is used in all of the following.…”

Section: Time Transfermentioning

confidence: 99%

“…The case of the coupling of time discretizations has been handled in [5]. In the following, an identical framework is used for defining space transfer operators.…”

Section: Dealing With Different Discretizationsmentioning

confidence: 99%

“…The corresponding time transfer operators (detailed in [5]) will be denoted in the following by p 12 for a transfer operator from time discretization T 2 -T 1 .…”

Section: Time Transfermentioning

confidence: 99%

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A computational strategy for thermo‐poroelastic structures with a time–space interface coupling

Néron

Dureisseix

2008

Numerical Meth Engineering

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International audienceThis paper deals with a computational strategy suitable for the simulation of multiphysics problems, based on the Large Time INcrement (LATIN) method. The simulation of such problems must encounter the possible different time and space scales which usually arise with the different physics. Herein, we focus on using different time and space discretizations for each physics by introducing an interface with its own discretization. The feasibility of both a time and space couplings is exemplified on a nonlinear 3-physics strongly coupled problem: the thermal / fluid / structure interaction in a thermo-poroelastic structure

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Section: Dealing With Different Discretizationsmentioning

confidence: 97%

Section: Simulation Of Coupled Multiphysics Problemsmentioning

confidence: 99%

Section: Time Transfermentioning

confidence: 99%

“…The case of the coupling of time discretizations has been handled in [5]. In the following, an identical framework is used for defining space transfer operators.…”

Section: Dealing With Different Discretizationsmentioning

confidence: 99%

“…The corresponding time transfer operators (detailed in [5]) will be denoted in the following by p 12 for a transfer operator from time discretization T 2 -T 1 .…”

Section: Time Transfermentioning

confidence: 99%

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A computational strategy for thermo‐poroelastic structures with a time–space interface coupling

Néron

Dureisseix

2008

Numerical Meth Engineering

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Model Reduction Methods

Chinesta

Huerta

Rozza

et al. 2017

Encyclopedia of Computational Mechanics Second Edition

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This chapter presents an overview of model order reduction – a new paradigm in the field of simulation‐based engineering sciences, and one that can tackle the challenges and leverage the opportunities of modern ICT technologies. Despite the impressive progress attained by simulation capabilities and techniques, a number of challenging problems remain intractable. These problems are of different nature, but are common to many branches of science and engineering. Among them are those related to high‐dimensional problems, problems involving very different time scales, models defined in degenerate domains with at least one of the characteristic dimensions much smaller than the others, model requiring real‐time simulation, and parametric models. All these problems represent a challenge for standard mesh‐based discretization techniques; yet the ability to solve these problems efficiently would open unexplored routes for real‐time simulation, inverse analysis, uncertainty quantification and propagation, real‐time optimization, and simulation‐based control – critical needs in many branches of science and engineering. Model order reduction offers new simulation alternatives by circumventing, or at least alleviating, otherwise intractable computational challenges. In the present chapter, we revisit three of these model reduction techniques: proper orthogonal decomposition, proper generalized decomposition, and reduced basis methodologies.

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Proper generalized decomposition of time‐multiscale models

Ammar

Chinesta

Cueto

et al. 2011

Numerical Meth Engineering

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. SUMMARYModels encountered in computational mechanics could involve many time scales. When these time scales cannot be separated, one must solve the evolution model in the entire time interval by using the finest time step that the model implies. In some cases, the solution procedure becomes cumbersome because of the extremely large number of time steps needed for integrating the evolution model in the whole time interval.In this paper, we considered an alternative approach that lies in separating the time axis (one-dimensional in nature) in a multidimensional time space. Then, for circumventing the resulting curse of dimensionality, the proper generalized decomposition was applied allowing a fast solution with significant computing time savings with respect to a standard incremental integration.

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A computational strategy for poroelastic problems with a time interface between coupled physics

Cited by 19 publications

References 34 publications

A computational strategy for thermo‐poroelastic structures with a time–space interface coupling

A computational strategy for thermo‐poroelastic structures with a time–space interface coupling

Model Reduction Methods

Proper generalized decomposition of time‐multiscale models

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