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Model order reduction (MOR) methods that are designed to preserve structural features of a given full order model (FOM) often suffer from a lower accuracy when compared to their non-structure-preserving counterparts. In this paper, we…

Systems and Control · Electrical Eng. & Systems 2022-05-17 Paul Schwerdtner , Matthias Voigt

Linear reduced-order modeling (ROM) is widely used for efficient simulation of deformation dynamics, but its accuracy is often limited by the fixed linearization of the reduced mapping. We propose a new adaptive strategy for linear ROM that…

Graphics · Computer Science 2025-10-01 Yutian Tao , Maurizio Chiaramonte , Pablo Fernandez

Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems with low-dimensional models. Nevertheless,…

Systems and Control · Electrical Eng. & Systems 2024-10-30 Joseph Lorenzetti , Andrew McClellan , Charbel Farhat , Marco Pavone

The investigation of fluid-solid systems is very important in a lot of industrial processes. From a computational point of view, the simulation of such systems is very expensive, especially when a huge number of parametric configurations…

We treat the accurate simulation of the calcination reaction in particles, where the particles are large and, thus, the inner-particle processes must be resolved. Because these processes need to be described with coupled partial…

Fluid Dynamics · Physics 2023-11-28 Lucas Reineking , Torben Bergold , Enric Illana , Viktor Scherer , Martin Mönnigmann

This work proposes a new framework of model reduction for parametric complex systems. The framework employs a popular model reduction technique dynamic mode decomposition (DMD), which is capable of combining data-driven learning and physics…

Numerical Analysis · Mathematics 2022-04-21 Hannah Lu , Daniel M. Tartakovsky

Minimization of energy in gradient systems leads to formation of oscillatory and Turing patterns in reaction-diffusion systems. These patterns should be accurately computed using fine space and time meshes over long time horizons to reach…

Numerical Analysis · Mathematics 2018-11-28 Tuğba Akman Yıldız , Murat Uzunca , Bülent Karasözen

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 paper introduces a new framework for constructing the Discrete Empirical Interpolation Method DEIM projection operator. The interpolation node selection procedure is formulated using the QR factorization with column pivoting, and it…

Numerical Analysis · Computer Science 2016-09-26 Zlatko Drmac , Serkan Gugercin

In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two…

Numerical Analysis · Mathematics 2024-03-12 Elena Zappon , Andrea Manzoni , Paola Gervasio , Alfio Quarteroni

To speed-up the solution to parametrized differential problems, reduced order models (ROMs) have been developed over the years, including projection-based ROMs such as the reduced-basis (RB) method, deep learning-based ROMs, as well as…

Numerical Analysis · Mathematics 2022-02-08 Ludovica Cicci , Stefania Fresca , Andrea Manzoni

Polymer based organic photovoltaic (OPV) technology offers a relatively inexpensive option for solar energy conversion provided its efficiency increases beyond the current level (6-7%) along with significant improvements in operational…

Materials Science · Physics 2015-03-17 Biswajit Ray , Pradeep R. Nair , Muhammad A. Alam

A state-space representation of water quality dynamics describing disinfectant (e.g., chlorine) transport dynamics in drinking water distribution networks has been recently proposed. Such representation is a byproduct of space- and…

Systems and Control · Electrical Eng. & Systems 2022-06-15 Shen Wang , Ahmad F. Taha , Ankush Chakrabarty , Lina Sela , Ahmed Abokifa

Feedback control synthesis for nonlinear, parameter-dependent fluid flow control problems is considered. The optimal feedback law requires the solution of the Hamilton-Jacobi-Bellman (HJB) PDE suffering the curse of dimensionality. This is…

Optimization and Control · Mathematics 2023-11-29 Sergey Dolgov , Dante Kalise , Luca Saluzzi

Direct numerical simulation of dynamical systems is of fundamental importance in studying a wide range of complex physical phenomena. However, the ever-increasing need for accuracy leads to extremely large-scale dynamical systems whose…

Dynamical Systems · Mathematics 2015-03-04 Jeff T. Borggaard , Serkan Gugercin

In course of this work, we examine the process of plastic profile extrusion, where a polymer melt is shaped inside the so-called extrusion die and fixed in its shape by solidification in the downstream calibration unit. More precise, we…

Numerical Analysis · Mathematics 2022-09-08 Daniel Hilger , Norbert Hosters

Parameters in mathematical models for glioblastoma multiforme (GBM) tumour growth are highly patient specific. Here we aim to estimate parameters in a Cahn-Hilliard type diffuse interface model in an optimised way using model order…

Numerical Analysis · Mathematics 2023-07-19 Abramo Agosti , Pasquale Ciarletta , Harald Garcke , Michael Hinze

Thermomechanical stress induced by through-silicon vias (TSVs) plays an important role in the performance and reliability analysis of 2.5D/3D ICs. While the finite element method (FEM) adopted by commercial software can provide accurate…

Computational Engineering, Finance, and Science · Computer Science 2024-11-20 Tianxiang Zhu , Qipan Wang , Yibo Lin , Runsheng Wang , Ru Huang

Systems of differential-algebraic equations (DAEs) represent a widespread formalism in the modeling of constrained mechanical systems and electrical networks. Due to the automatic, object-oriented generation of the equations of motion and…

Numerical Analysis · Mathematics 2015-08-31 Alessandro Castagnotto , Heiko K. F. Panzer , Klaus-Dieter Reinsch , Boris Lohmann

The discrete empirical interpolation method (DEIM) is a well-established approach, widely used for state reconstruction using sparse sensor/measurement data, nonlinear model reduction, and interpretable feature selection. We introduce the…

Numerical Analysis · Mathematics 2024-10-21 Sridhar Chellappa , Lihong Feng , Peter Benner
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