Results 11 to 20 of about 4,521,373 (282)
Reduced order models for thermally coupled low Mach flows [PDF]
Advanced Modeling and Simulation in Engineering Sciences, 2018 In this paper we present a collection of techniques used to formulate a projection-based reduced order model (ROM) for zero Mach limit thermally coupled Navier–Stokes equations. The formulation derives from a standard proper orthogonal decomposition (POD)
Ricardo Reyes +3 more
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Computational design of patterned interfaces using reduced order models. [PDF]
Sci Rep, 2014 Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids.
Vattré AJ +3 more
europepmc +4 more sources
Reduced-order modelling numerical homogenization [PDF]
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2014 A general framework to combine numerical homogenization and reduced-order modelling techniques for partial differential equations (PDEs) with multiple scales is described. Numerical homogenization methods are usually efficient to approximate the effective solution of PDEs with multiple scales.
Abdulle Assyr, Bai Yun
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Learning stable reduced-order models for hybrid twins
Data-Centric Engineering, 2021 The concept of “hybrid twin” (HT) has recently received a growing interest thanks to the availability of powerful machine learning techniques. This twin concept combines physics-based models within a model order reduction framework—to obtain real-time ...
Abel Sancarlos +6 more
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Topology Optimization Based Material Design for 3D Domains Using MATLAB
Applied Sciences, 2022 In this work, a simple, easy to use MATLAB code is presented for the optimal design of materials for 3D domains. For the optimal design of materials, the theoretical framework of topology optimization and that of homogenization were utilized to develop a
George Kazakis, Nikos D. Lagaros
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Wall‐based reduced‐order modelling [PDF]
International Journal for Numerical Methods in Fluids, 2015 SummaryIn this work, we propose a novel approach to model order reduction for incompressible fluid flows, which focuses on the spatio‐temporal description of the stresses on the surface of a body, that is, of the wall shear stress and of the wall pressure.
Lasagna, Davide, Tutty, Owen
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Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey
Fluids, 2020 Reduced order models (ROMs) are computational models whose dimension is significantly lower than those obtained through classical numerical discretizations (e.g., finite element, finite difference, finite volume, or spectral methods).
Changhong Mou +4 more
doaj +1 more source
Learning reduced-order models for cardiovascular simulations with graph neural networks. [PDF]
Comput Biol MedPegolotti L +6 more
europepmc +2 more sources
Linear Reduced-Order Model Predictive Control
IEEE Transactions on Automatic Control, 2022 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, high-dimensional models arise in many settings, for example discretization methods for generating finite-dimensional ...
Joseph Lorenzetti +3 more
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Approximate deconvolution reduced order modeling [PDF]
Computer Methods in Applied Mechanics and Engineering, 2017 This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal decomposition(POD) is used to define the ROM basis and a POD differential filter is used to define the large ROM structures.
Xie, X. +3 more
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