Model order reduction of coupled thermo-hydro-mechanical processes in geo-environmental applications

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Université libre de BruxellesIn a large number of geo-environmental applications, it is essential to model coupled processes that depend on several design parameters such as material properties and geometrical features. Thermo-hydro-mechanical (THM) processes are, among others, key effects to consider in critical applications such as deep geological repository of hazardous waste. This thesis proposes novel model order reduction strategies to evaluate the thermo-hydro-mechanical response of the material, taking into account the complexities involved in the coupled processes for such applications. To include variability of some design parameters, an a-posteriori model order reduction approach with reduced basis methods is applied to solve the high-dimensional parametric THM system. The reduction is based on an offline-online stage strategy. In the offline stage, reduced subspaces are constructed by a greedy adaptive procedure and in the online stage, multi-subspace projection is performed to quickly obtain the coupled THM response at any value of the design parameter. At the core of the greedy adaptive strategy is a goal-oriented error estimator that guides the selection of optimal design parameters where snapshots are evaluated. To tackle nonlinearity in the form of elasto-plastic material behaviour, the multi-subspace reduced basis method is combined with sub-structuring by domain decomposition. The effectiveness of the model reduction strategies are demonstrated on inverse problems involving large-scale geomodels that depict the coupled response of host rocks in potential deep geological repository sites. Two types of scenarios are considered: (i) the host rock undergoing geomorphological process is investigated as glacier advances over it for a period lasting over thousands of years and (ii) the clay response of an underground research laboratory is modelled numerically to support and validate in-situ heating experiments.En un gran número de aplicaciones geoambientales, es esencial modelar procesos acoplados que dependen de varios parámetros de diseño, como las propiedades de los materiales y las características geométricas. Los procesos termohidromecánicos (THM) son, entre otros, efectos clave a considerar en aplicaciones críticas como los depósitos geológicos profundos de residuos peligrosos. Esta tesis propone novedosas estrategias de reducción de orden del modelo para evaluar la respuesta termo-hidromecánica del material, teniendo en cuenta las complejidades que implican los procesos acoplados para dichas aplicaciones. Para incluir la variabilidad de algunos parámetros de diseño, se aplica un enfoque de reducción de orden del modelo a-posteriori con métodos de base reducida para resolver el sistema paramétrico THM de alta dimensión. La reducción se basa en una estrategia de etapas offline-online. En la etapa offline, los subespacios reducidos se construyen mediante un procedimiento adaptativo codicioso y en la etapa online, se realiza una proyección multisubespacio para obtener rápidamente la respuesta THM acoplada a cualquier valor del parámetro de diseño. El núcleo de la estrategia adaptativa 'greedy' es un 'goal-oriented error estimator' a objetivos que guía la selección de los parámetros de diseño óptimos donde se evalúan las 'snapshots'. Para hacer frente a la no linealidad en forma de comportamiento elastoplástico del material, se combina el método de bases reducidas multisuperficie con 'domain decomposition sub-structuring'. La eficacia de las estrategias de reducción de modelos se demuestra en problemas inversos de problemas inversos que implican geomodelos a gran escala que representan la respuesta acoplada de las rocas anfitrionas en posibles emplazamientos de depósitos geológicos profundos. Se consideran dos tipos de escenarios: (i) se investiga la roca sometida a un proceso geomorfológico a medida que el glaciar avanza sobre ella durante un período de miles de años y (ii) se modela numéricamente la respuesta de la arcilla de un laboratorio de investigación subterráneo para apoyar y validar los experimentos de "in situ heating"Postprint (published version

Model order reduction of coupled thermo-hydro-mechanical processes in geo-environmental applications

In a large number of geo-environmental applications, it is essential to model coupled processes that depend on several design parameters such as material properties and geometrical features. Thermo-hydro-mechanical (THM) processes are, among others, key effects to consider in critical applications such as deep geological repository of hazardous nuclear waste. This thesis proposes novel model order reduction strategies to evaluate the thermo-hydro-mechanical response of porous media, taking into account the complexities involved in coupled processes for such applications. An a-posteriori model order reduction approach using reduced basis methods is applied to tackle the high-dimensional parametric THM system. The reduction is based on an offline-online stage strategy. In the offline stage, reduced subspaces are constructed by a greedy adaptive procedure and in the online stage, multi-subspace projection is performed to quickly obtain the coupled THM response at any value of the design parameter. The effectiveness of the model reduction strategies is demonstrated through realistic parametrized problems in large-scale geomodels depicting the coupled processes in potential deep geological repository sites.Doctorat en Sciences de l'ingénieur et technologieinfo:eu-repo/semantics/nonPublishe

Reduced Order Modelling for Coupled Systems in Geological Porous Media

info:eu-repo/semantics/nonPublishe

INVERSE PROBLEMS FOR TRANSIENT COUPLED THERMO-HYDRO-MECHANICAL SYSTEMS USING GOAL-ORIENTED REDUCED BASIS APPROXIMATION

info:eu-repo/semantics/nonPublishe

Building a certified reduced basis for coupled thermo-hydro-mechanical systems with goal-oriented error estimation

This is a post-peer-review, pre-copyedit version of an article published in Computational mechanics. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00466-020-01865-7A goal-oriented a-posteriori error estimator is developed for transient coupled thermo-hydro-mechanical (THM) parametric problems solved with a reduced basis approximation. The estimator assesses the error in some specific Quantity of Interest (QoI). The goal-oriented error estimate is derived based on explicitly-computed weak residual of the primal problem and implicitly-computed adjoint solution associated with the QoI. The time-dependence of the coupled THM system poses an additional complexity as the auxiliary adjoint problem evolves backwards in time. The error estimator guides a greedy adaptive procedure that constructs progressively an optimal reduced basis by smartly selecting snapshot points over a given parametric training sample. The reduced basis obtained is used to drastically reduce the coupled system spatial degrees of freedom by several orders of magnitude. The computational gain obtained from the developed methodology is demonstrated through applications in 2D and 3D parametrized problems simulating the evolution of coupled THM processes in rock masses.Peer ReviewedPostprint (author's final draft

Building a Certified Reduced Basis for Transient Coupled Problems

info:eu-repo/semantics/nonPublishe

Reduced basis approximation and goal-oriented error estimation for transient coupled thermo-hydro-mechanical systems

info:eu-repo/semantics/publishe

Building a Certified Reduced Basis for Coupled Thermo- Hydro-Mechanical Systems with Goal-Oriented Error Estimation

A goal-oriented a-posteriori error estimator is developed for transient coupled Thermo-Hydro-Mechanical (THM) parametric problems solved with a reduced basis approximation. The estimator assesses the error in some specific Quantity of Interest (QoI). The goal-oriented error estimate is derived based on explicitly-computed weak residual of the primal problem and implicitly-computed adjoint solution associated with the QoI. The time-dependence of the coupled THM system poses an additional complexity as the auxiliary adjoint problem evolves backwards in time. The error estimator guides a greedy adaptive procedure that constructs progressively an optimal reduced basis by smartly selecting snapshot points over a given parametric training sample. The reduced basis obtained is used to drastically reduce the coupled system spatial degrees of freedom by several orders of magnitude. The computational gain obtained from the developed methodology is demonstrated through applications in 2D and 3D parametrized problems simulating the evolution of coupled THM processes in rock masses.info:eu-repo/semantics/publishe

Using reduced basis approximation for efficient surrogate-based inverse identification of thermo-hydro-mechanical parameters from an in situ heating test

The version of record is available online at: http://dx.doi.org/10.1007/s00603-022-02925-5In this paper, a reduced-order model built from the reduced basis (RB) method is used as a surrogate for an inverse identification problem related to coupled thermo-hydro-mechanical (THM) processes. The RB space—spanned by solutions of the governing THM equations—is constructed using a greedy adaptive procedure guided by an a posteriori error estimator that selects the optimal snapshot points in a given parametric space. The RB model is assessed in terms of accuracy and computational cost reduction for the three-dimensional transient coupled problem described by the ATLAS III small-scale in situ heating test. The substantial system size reduction and the associated significant computational gain result in a surrogate model suitable for parameter identification procedures in the Boom Clay material. The effectiveness of the proposed strategy is demonstrated by performing inverse analysis based on direct-search and genetic algorithm (GA) optimization supported by real sensor measurement data where 800 times faster computational speed-up was achieved.We acknowledge the funding support from the European Commission Education, Audiovisual and Culture Executive Agency (EACEA) under Erasmus Mundus Joint Doctorate Simulation in Engineering and Entrepreneurship Development (SEED), FPA 2013-0043 and SCK CEN for funding the 4th year PhD study of the first author. S. Zlotnik and P. Díez would like to thank the funding from the Generalitat de Catalunya 2017-SGR-1278, the project DPI2017-85139-C2-2-R funded by the Spanish Ministry and the project H2020-RISE MATHROCKS GA no. 777778.Peer ReviewedPostprint (author's final draft

Using Reduced Basis Approximation for Efficient Surrogate-based Inverse Identification of Thermo-Hydro-Mechanical Parameters from an In-situ Heating Test

In this paper, a reduced order model built from the reduced basis (RB) method is used as a surrogate for an inverse identification problem related to coupled thermo-hydro-mechanical (THM) processes. The RB space - spanned by solutions of the governing THM equations - is constructed using a greedy adaptive procedure guided by an a-posteriori error estimator that selects the optimal snapshot points in a given parametric space. The RB model is assessed in terms of accuracy and computational cost reduction for the three-dimensional transient coupled problem described by the ATLAS III small scale in-situ heating test. The substantial system size reduction and the associated significant computational gain result in a surrogate model suitable for parameter identification procedures in the Boom Clay material. The effectiveness of the proposed strategy is demonstrated by performing inverse analysis based on direct-search and genetic algorithm (GA) optimization supported by real sensor measurement data where 800 times faster computational speed-up was achieved.info:eu-repo/semantics/publishe