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 inJournal of numerical mathematics Vol. 33; no. 1; pp. 1 - 35
Main Authors Zoccolan, Fabio, Strazzullo, Maria, Rozza, Gianluigi
Format Journal Article
LanguageEnglish
Published Berlin De Gruyter 26.03.2025
Walter de Gruyter GmbH
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ISSN1570-2820
1569-3953
DOI10.1515/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.
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
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  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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Snippet In this work, we analyze Parametrized Advection-Dominated distributed Optimal Control Problems with random inputs in a Reduced Order Model (ROM) context. All...
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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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https://www.proquest.com/docview/3172250417
Volume 33
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