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Within the environmental context, numerical modeling is a promising approach to assessing the energy efficiency of buildings. Resilient buildings need to be designed, and capable of adapting to future extreme heat. Simulations are required…

Computational Engineering, Finance, and Science · Computer Science 2022-06-20 Julien Berger , Cyrille Allery , Anaïs Machard

By combining different ideas, a general and efficient protocol to deal with discontinuous phase transitions at low temperatures is proposed. For small $T$'s, it is possible to derive a generic analytic expression for appropriate order…

Statistical Mechanics · Physics 2015-06-03 C. E. Fiore , M. G. E. da Luz

In this contribution, we coupled the isogeometric analysis to a reduced order modelling technique in order to provide a computationally efficient solution in parametric domains. In details, we adopt the free-form deformation method to…

Numerical Analysis · Mathematics 2020-11-23 Fabrizio Garotta , Nicola Demo , Marco Tezzele , Massimo Carraturo , Alessandro Reali , Gianluigi Rozza

This paper offers an approach to deal with parametrized nonlinear strongly coupled thermo-poroelasticity problems. The approach uses the LATIN-PGD method and extends previous work in multiphysics problems. Proper Generalized Decomposition…

Classical Physics · Physics 2025-08-28 Elise Foulatier , David Néron , François Louf , Pierre-Alain Boucard

We propose in this paper a Proper Generalized Decomposition (PGD) approach for the solution of problems in linear elastodynamics. The novelty of the work lies in the development of weak formulations of the PGD problems based on the…

Computational Engineering, Finance, and Science · Computer Science 2023-01-26 Clément Vella , Serge Prudhomme

A parametric reduced order model based on proper orthogonal decomposition with Galerkin projection has been developed and applied for the modeling of heat transport in T-junction pipes which are widely found in nuclear power plants. Thermal…

Computational Physics · Physics 2019-01-29 Sokratia Georgaka , Giovanni Stabile , Gianluigi Rozza , Michael J Bluck

This investigation is motivated by the problem of optimal design of cooling elements in modern battery systems. We consider a simple model of two-dimensional steady-state heat conduction described by elliptic partial differential equations…

Numerical Analysis · Mathematics 2013-07-05 Xiaohui Peng , Katsiaryna Niakhai , Bartosz Protas

Partial differential equations can be used to model many problems in several fields of application including, e.g., fluid mechanics, heat and mass transfer, and electromagnetism. Accurate discretization methods (e.g., finite element or…

Numerical Analysis · Mathematics 2022-03-18 Pierfrancesco Siena , Michele Girfoglio , Gianluigi Rozza

Thermal tomography is an imaging technique for deducing information about the internal structure of a physical body from temperature measurements on its boundary. This work considers time-dependent thermal tomography modeled by a parabolic…

Numerical Analysis · Mathematics 2017-07-25 Nuutti Hyvönen , Lauri Mustonen

The proper generalized decomposition is applied to a static electrothermal model subject to uncertainties. A reduced model that circumvents the curse of dimensionality is obtained. The quadratic electrothermal coupling term is non-standard…

Computational Engineering, Finance, and Science · Computer Science 2019-03-25 Alexander Krimm , Thorben Casper , Sebastian Schöps , Herbert De Gersem , Ludovic Chamoin

This contribution focuses on the development of Model Order Reduction (MOR) for one-way coupled steady state linear thermomechanical problems in a finite element setting. We apply Proper Orthogonal Decomposition (POD) for the computation of…

This work introduces an ensemble parameter estimation framework that enables the Lumped Parameter Linear Superposition (LPLSP) method to generate reduced order thermal models from a single transient dataset. Unlike earlier implementations…

Numerical Analysis · Mathematics 2026-05-26 Neelakantan Padmanabhan

In the present work, a new methodology is proposed for building surrogate parametric models of engineering systems based on modular assembly of pre-solved modules. Each module is a generic parametric solution considering parametric…

Computational Engineering, Finance, and Science · Computer Science 2024-03-15 Angelo Pasquale , Mohammad-Javad Kazemzadeh-Parsi , Daniele Di Lorenzo , Victor Champaney , Amine Ammar , Francisco Chinesta

A reduced-order model based on Proper Orthogonal Decomposition (POD) is proposed for the bidomain equations of cardiac electrophysiology. Its accuracy is assessed through electrocardiograms in various configurations, including myocardium…

Numerical Analysis · Mathematics 2012-07-23 Muriel Boulakia , Elisa Schenone , Jean-Frédéric Gerbeau

Reduced basis approximations of Optimal Control Problems (OCPs) governed by steady partial differential equations (PDEs) with random parametric inputs are analyzed and constructed. Such approximations are based on a Reduced Order Model,…

Numerical Analysis · Mathematics 2023-08-08 Giuseppe Carere , Maria Strazzullo , Francesco Ballarin , Gianluigi Rozza , Rob Stevenson

In this paper, a parametric model order reduction (pMOR) technique is proposed to find a simplified system representation of a large-scale and complex thermal system. The main principle behind this technique is that any change of the…

Systems and Control · Computer Science 2018-03-15 Daming Lou , Siep Weiland

The estimation of wall thermal properties by \emph{in situ} measurement enables to increase the reliability of the model predictions for building energy efficiency. Nevertheless, retrieving the unknown parameters has an important…

Computational Engineering, Finance, and Science · Computer Science 2021-11-18 Julien Berger , Benjamin Kadoch

An approach to derive low-complexity models describing thermal radiation for the sake of simulating the behavior of electric arcs in switchgear systems is presented. The idea is to approximate the (high dimensional) full-order equations,…

Optimization and Control · Mathematics 2015-12-09 Lorenzo Fagiano , Rudolf Gati

We propose in this paper a Proper Generalized Decomposition (PGD) solver for reduced-order modeling of linear elastodynamic problems. It primarily focuses on enhancing the computational efficiency of a previously introduced PGD solver based…

Computational Engineering, Finance, and Science · Computer Science 2024-05-15 Clément Vella , Pierre Gosselet , Serge Prudhomme

We present an effective method for computing parametric primary decomposition via comprehensive Gr\"obner systems. In general, it is very difficult to compute a parametric primary decomposition of a given ideal in the polynomial ring with…

Symbolic Computation · Computer Science 2024-08-29 Yuki Ishihara , Kazuhiro Yokoyama
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