Results 31 to 40 of about 3,862 (118)
Improving reduced-order models through nonlinear decoding of projection-dependent outputs
Patterns, 2023 Summary: A fundamental hindrance to building data-driven reduced-order models (ROMs) is the poor topological quality of a low-dimensional data projection.
Kamila Zdybał +2 more
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Generative adversarial reduced order modelling
Scientific ReportsAbstractIn this work, we present GAROM, a new approach for reduced order modeling (ROM) based on generative adversarial networks (GANs). GANs attempt to learn to generate data with the same statistics of the underlying distribution of a dataset, using two neural networks, namely discriminator and generator.
Coscia, Dario +2 more
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Regularization method for calibrated POD reduced-order models
MATEC Web of Conferences, 2014 In this work we present a regularization method to improve the accuracy of reduced-order models based on Proper Orthogonal Decomposition. The bench mark configuration retained corresponds to a case of relatively simple dynamics: a two-dimensional flow ...
El Majd Badr Abou, Cordier Laurent
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New Regularization Method for Calibrated POD Reduced-Order Models
Mathematical Modelling and Analysis, 2016 Reduced-order models based on Proper orthogonal decomposition are known to suffer from a lack of accuracy due to the truncation effect introduced by keeping only the most energetic modes.
Badr Abou El Majd, Laurent Cordier
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Hybrid Neural Network Reduced Order Modelling for Turbulent Flows with Geometric Parameters
Fluids, 2021 Geometrically parametrized partial differential equations are currently widely used in many different fields, such as shape optimization processes or patient-specific surgery studies.
Matteo Zancanaro +4 more
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Reduced order models based on pod method for schrödinger equations
Mathematical Modelling and Analysis, 2013 Reduced-order models (ROM) are developed using the proper orthogonal decomposition (POD) for one dimensional linear and nonlinear Schrödinger equations. The main aim of this paper is to study the accuracy and robustness of the ROM approximations.
Gerda Jankevičiutė +3 more
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Characteristics of linear modal instabilities in hypersonic flows with detached shock waves
Results in Engineering, 2021 A preliminary study on the linear instabilities present in a defined hypersonic flow over a blunt object is analyzed in this work. Such flow instabilities are defined in the detached shock wave and the defined shock region between the shock wave and the ...
José M. Pérez, Cristina Jimenez
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Reduced order Galerkin models of flow around NACA‐0012 airfoil
Mathematical Modelling and Analysis, 2008 The construction of low‐dimensional models of the flow, containing only reduced number of degrees of freedom, is the essential prerequisite of closed‐loop control of that flow.
Witold Stankiewicz +3 more
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Towards Reduced-Order Models of Solid Oxide Fuel Cell
Complexity, 2018 The objective of this work is to find precise reduced-order discrete-time models of a solid oxide fuel cell, which is a multiple-input multiple-output dynamic process.
Maciej Ławryńczuk
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Multiphase flow applications of nonintrusive reduced-order models with Gaussian process emulation
Data-Centric Engineering, 2022 Reduced-order models (ROMs) are computationally inexpensive simplifications of high-fidelity complex ones. Such models can be found in computational fluid dynamics where they can be used to predict the characteristics of multiphase flows.
Themistoklis Botsas +3 more
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