Stabilized weighted reduced order methods for parametrized advection-dominated optimal control problems governed by partial differential equations with random inputs
In this work, we analyze Parametrized Advection-Dominated distributed Optimal Control Problems with random inputs in a Reduced Order Model (ROM) context. All the simulations are initially based on a finite element method (FEM) discretization; moreover, a is considered when dealing with unsteady case...
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| Published in | Journal of numerical mathematics Vol. 33; no. 1; pp. 1 - 35 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin
De Gruyter
26.03.2025
Walter de Gruyter GmbH |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1570-2820 1569-3953 |
| DOI | 10.1515/jnma-2023-0006 |
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| Abstract | In this work, we analyze Parametrized Advection-Dominated distributed Optimal Control Problems with random inputs in a Reduced Order Model (ROM) context. All the simulations are initially based on a finite element method (FEM) discretization; moreover, a
is considered when dealing with unsteady cases. To overcome numerical instabilities that can occur in the optimality system for high values of the Péclet number, we consider a Streamline Upwind Petrov–Galerkin technique applied in an optimize-then-discretize approach. We combine this method with the ROM framework in order to consider two possibilities of stabilization: Offline-Only stabilization and Offline-Online stabilization. Moreover we consider random parameters and we use a
algorithm in a partitioned approach to deal with the issue of uncertainty quantification. Several quadrature techniques are used to derive weighted ROMs: tensor rules, isotropic sparse grids, Monte-Carlo and quasi Monte-Carlo methods. We compare all the approaches analyzing relative errors between the FEM and ROM solutions and the computational efficiency based on the speedup-index. |
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| AbstractList | In this work, we analyze Parametrized Advection-Dominated distributed Optimal Control Problems with random inputs in a Reduced Order Model (ROM) context. All the simulations are initially based on a finite element method (FEM) discretization; moreover, a
is considered when dealing with unsteady cases. To overcome numerical instabilities that can occur in the optimality system for high values of the Péclet number, we consider a Streamline Upwind Petrov–Galerkin technique applied in an optimize-then-discretize approach. We combine this method with the ROM framework in order to consider two possibilities of stabilization: Offline-Only stabilization and Offline-Online stabilization. Moreover we consider random parameters and we use a
algorithm in a partitioned approach to deal with the issue of uncertainty quantification. Several quadrature techniques are used to derive weighted ROMs: tensor rules, isotropic sparse grids, Monte-Carlo and quasi Monte-Carlo methods. We compare all the approaches analyzing relative errors between the FEM and ROM solutions and the computational efficiency based on the speedup-index. In this work, we analyze Parametrized Advection-Dominated distributed Optimal Control Problems with random inputs in a Reduced Order Model (ROM) context. All the simulations are initially based on a finite element method (FEM) discretization; moreover, a space-time approach is considered when dealing with unsteady cases. To overcome numerical instabilities that can occur in the optimality system for high values of the Péclet number, we consider a Streamline Upwind Petrov–Galerkin technique applied in an optimize-then-discretize approach. We combine this method with the ROM framework in order to consider two possibilities of stabilization: Offline-Only stabilization and Offline-Online stabilization. Moreover we consider random parameters and we use a weighted Proper Orthogonal Decomposition algorithm in a partitioned approach to deal with the issue of uncertainty quantification. Several quadrature techniques are used to derive weighted ROMs: tensor rules, isotropic sparse grids, Monte-Carlo and quasi Monte-Carlo methods. We compare all the approaches analyzing relative errors between the FEM and ROM solutions and the computational efficiency based on the speedup-index. |
| Author | Zoccolan, Fabio Strazzullo, Maria Rozza, Gianluigi |
| Author_xml | – sequence: 1 givenname: Fabio orcidid: 0000-0002-5845-8415 surname: Zoccolan fullname: Zoccolan, Fabio email: fabio.zoccolan@epfl.ch organization: Institut de Mathématiques, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland – sequence: 2 givenname: Maria orcidid: 0000-0003-1245-271X surname: Strazzullo fullname: Strazzullo, Maria email: maria.strazzullo@polito.it organization: DISMA, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy – sequence: 3 givenname: Gianluigi orcidid: 0000-0002-0810-8812 surname: Rozza fullname: Rozza, Gianluigi email: gianluigi.rozza@sissa.it organization: mathLab, Mathematics Area, SISSA, via Bonomea 265, I-34136 Trieste, Italy |
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| SubjectTerms | 49J20 49M41 60H25 60H35 65M60 Advection Algorithms Finite element method Mathematics Monte Carlo simulation Optimal control Optimization Parameterization Partial differential equations Peclet number Proper Orthogonal Decomposition Quadratures random inputs reduced order methods Reduced order models Stabilization Tensors time-dependent parametrized optimal control problem uncertainty quantification weighted proper orthogonal decomposition |
| Title | Stabilized weighted reduced order methods for parametrized advection-dominated optimal control problems governed by partial differential equations with random inputs |
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