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Related papers: A Reduced Order Model for Joint Assemblies by Hype…

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Projection-based reduced-order models (PROMs) have demonstrated accuracy, reliability, and robustness in approximating high-dimensional, differential equation-based computational models across many applications. For this reason, it has been…

Numerical Analysis · Mathematics 2025-05-05 Calista Biondic , Siva Nadarajah

We propose an efficient hyper-reduced order model (HROM) designed for segregated finite-volume solvers in geometrically parametrized problems. The method follows a discretize-then-project strategy: the full-order operators are first…

Numerical Analysis · Mathematics 2026-01-13 Valentin Nkana Ngan , Giovanni Stabile , Andrea Mola , Gianluigi Rozza

Reduced-order models that accurately abstract high fidelity models and enable faster simulation is vital for real-time, model-based diagnosis applications. In this paper, we outline a novel hybrid modeling approach that combines machine…

Signal Processing · Electrical Eng. & Systems 2020-03-06 Ion Matei , Johan de Kleer , Alexander Feldman , Rahul Rai , Souma Chowdhury

Common trends in model order reduction of large nonlinear finite-element-discretized systems involve the introduction of a linear mapping into a reduced set of unknowns, followed by Galerkin projection of the governing equations onto a…

Computational Engineering, Finance, and Science · Computer Science 2019-04-18 Shobhit Jain , Paolo Tiso

Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems. This paper applies machine learning techniques to improve…

Machine Learning · Computer Science 2015-11-11 Azam Moosavi , Razvan Stefanescu , Adrian Sandu

We propose an algorithm for the computational homogenization of locally periodic hyperelastic structures undergoing large deformations due to external quasi-static loading. The algorithm performs clustering of macroscopic deformations into…

Numerical Analysis · Mathematics 2026-02-26 Vladimír Lukeš , Eduard Rohan

The energy-conserving sampling and weighting (ECSW) method is a hyperreduction method originally developed for accelerating the performance of Galerkin projection-based reduced-order models (PROMs) associated with large-scale finite element…

Numerical Analysis · Mathematics 2020-08-10 Sebastian Grimberg , Charbel Farhat , Radek Tezaur , Charbel Bou-Mosleh

In this work we propose and analyze a novel Hybrid High-Order discretization of a class of (linear and) nonlinear elasticity models in the small deformation regime which are of common use in solid mechanics. The proposed method is valid in…

Numerical Analysis · Mathematics 2017-07-10 Michele Botti , Daniele Di Pietro , Pierre Sochala

Real applications in structural mechanics, where the dynamic behavior is linear, are rare. Usually, structures are made of components assembled together by means of joints whose behavior maybe highly nonlinear. Depending on the amount of…

Dynamical Systems · Mathematics 2018-11-26 Stefano Zucca , Christian M. Firrone

Numerical homogenization for mechanical multiscale modeling by means of the finite element method (FEM) is an elegant way of obtaining structure-property relations, if the behavior of the constituents of the lower scale is well understood.…

Numerical Analysis · Mathematics 2025-08-07 Nils Lange , Geralf Hütter , Bjoern Kiefer

We present a robust and efficient target-based mesh adaptation methodology, building on hybridized discontinuous Galerkin schemes for (nonlinear) convection-diffusion problems, including the compressible Euler and Navier-Stokes equations.…

Numerical Analysis · Mathematics 2014-11-12 Michael Woopen , Georg May , Jochen Schütz

We propose a new model reduction framework for problems that exhibit transport phenomena. As in the moving finite element method (MFEM), our method employs time-dependent transformation operators and, especially, generalizes MFEM to…

Numerical Analysis · Mathematics 2020-10-30 Felix Black , Philipp Schulze , Benjamin Unger

Recently, some hypergraph-based methods have been proposed to deal with the problem of model fitting in computer vision, mainly due to the superior capability of hypergraph to represent the complex relationship between data points. However,…

Computer Vision and Pattern Recognition · Computer Science 2020-02-14 Shuyuan Lin , Guobao Xiao , Yan Yan , David Suter , Hanzi Wang

High-resolution simulation models are essential for representing complex physical systems, yet their substantial computational cost severely limits the number of feasible high-fidelity (HF) evaluations. This problem is often addressed…

Methodology · Statistics 2026-04-21 Hossein Mohammadi

The vast majority of reduced-order models (ROMs) first obtain a low dimensional representation of the problem from high-dimensional model (HDM) training data which is afterwards used to obtain a system of reduced complexity. Unfortunately,…

Numerical Analysis · Mathematics 2023-09-14 Victor Zucatti , Matthew J. Zahr

This paper introduces the Fej\'er-monotone hybrid steepest descent method (FM-HSDM), a new member to the HSDM family of algorithms, for solving affinely constrained minimization tasks in real Hilbert spaces, where convex smooth and…

Optimization and Control · Mathematics 2018-04-11 Konstantinos Slavakis , Isao Yamada

We present a novel technique to significantly reduce the offline cost associated to non-intrusive nonlinear tensors identification in reduced order models (ROMs) of geometrically nonlinear, finite elements (FE)-discretized structural…

Numerical Analysis · Mathematics 2024-11-22 Alexander Saccani , Paolo Tiso

The recently developed generalized Fourier-Galerkin method is complemented by a numerical continuation with respect to the kinetic energy, which extends the framework to the investigation of modal interactions resulting in folds of the…

Numerical Analysis · Mathematics 2021-01-07 Malte Krack , Lars Panning-von Scheidt , Jörg Wallaschek

This paper presents a methodology that enables projection-based model reduction for black-box high-fidelity models such as commercial CFD codes. The methodology specifically addresses the situation where the high-fidelity model may be a…

Analysis of PDEs · Mathematics 2017-10-18 S. Ashwin Renganathan , Yingjie Liu , Dimitri N. Mavris

A multiscale (micro-to-macro) analysis is proposed for the prediction of the finite strain behavior of composites with hyperelastic constituents and embedded localized damage. The composites are assumed to possess periodic microstructure…

Materials Science · Physics 2020-10-20 Nathan Perchikov , Jacob Aboudi
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