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In this paper, we present a generic approach of a dynamical data-driven model order reduction technique for three-dimensional fluid-structure interaction problems. A low-order continuous linear differential system is identified from…

Computational Engineering, Finance, and Science · Computer Science 2023-01-25 Claire Dupont , Florian De Vuyst , Anne-Virginie Salsac

Real-world systems are often characterized by high-dimensional nonlinear dynamics, making them challenging to control in real time. While reduced-order models (ROMs) are frequently employed in model-based control schemes, dimensionality…

Systems and Control · Electrical Eng. & Systems 2023-09-13 John Irvin Alora , Luis A. Pabon , Johannes Köhler , Mattia Cenedese , Ed Schmerling , Melanie N. Zeilinger , George Haller , Marco Pavone

In this paper, we propose a nonintrusive filter-based stabilization of reduced order models (ROMs) for uncertainty quantification (UQ) of the time-dependent Navier-Stokes equations in convection-dominated regimes. We propose a novel…

Numerical Analysis · Mathematics 2018-10-23 M. Gunzburger , T. Iliescu , M. Mohebujjaman , M. Schneier

In this paper, we introduce a novel approach that combines multiresolution (MR) techniques with the flux reconstruction (FR) method to accurately and effciently simulate compressible flows. We achieve further enhancements in effciency…

Fluid Dynamics · Physics 2023-06-21 Yixuan Lian , Jinsheng Cai , Shucheng Pan

A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in…

General Relativity and Quantum Cosmology · Physics 2018-06-11 Dániel Barta , Mátyás Vasúth

In this paper, we present a brief tutorial on reduced order model (ROM) closures. First, we carefully motivate the need for ROM closure modeling in under-resolved simulations. Then, we construct step by step the ROM closure model by…

Numerical Analysis · Mathematics 2022-03-01 William Snyder , Changhong Mou , Honghu Liu , Omer San , Raffaella De Vita , Traian Iliescu

An adaptive approach to using reduced-order models as surrogates in PDE-constrained optimization is introduced that breaks the traditional offline-online framework of model order reduction. A sequence of optimization problems constrained by…

Optimization and Control · Mathematics 2014-07-30 Matthew J. Zahr , Charbel Farhat

Inferring unknown initial states in shock-dominated compressible flows from sparse and noisy measurements is a challenging ill-posed inverse problem due to nonlinear wave interactions and limited sensing. In this work, we develop a…

Machine Learning · Computer Science 2026-05-20 Bipin Tiwari , Muhammad Abid , Omer San

This study presents an artificial neural network and proper orthogonal decomposition (POD)-based reduced-order model (ROM) of turbulent flow around a finite wall-mounted square cylinder. The proposed model is suitable for turbulent wake…

Fluid Dynamics · Physics 2021-09-21 Mustafa Z. Yousif , Hee Chang Lim

A seismic wavefield reconstruction framework based on compressed sensing using the data-driven reduced-order model (ROM) is proposed and its characteristics are investigated through numerical experiments. The data-driven ROM is generated…

Continuum robots are advancing bronchoscopy procedures by accessing complex lung airways and enabling targeted interventions. However, their development is limited by the lack of realistic training and test environments: Real data is…

This paper presents the first high-order computational fluid dynamics (CFD) simulations of static and spinning golf balls at realistic flow conditions. The present results are shown to capture the complex fluid dynamics inside the dimples…

Fluid Dynamics · Physics 2018-06-04 Jacob Crabill , Freddie Witherden , Antony Jameson

Reduced-order models (ROMs) can efficiently simulate high-dimensional physical systems but lack robust uncertainty quantification methods. Existing approaches are frequently architecture- or training-specific, which limits flexibility and…

Machine Learning · Computer Science 2025-11-18 Jonas E. Katona , Emily K. de Jong , Nipun Gunawardena

The time discrete scheme of characteristics type is especially effective for convection-dominated diffusion problems. The scheme has been used in various engineering areas with different approximations in spatial direction. The lowest-order…

Numerical Analysis · Mathematics 2022-04-28 W. Sun

The goal of this paper is to assess the utility of Reduced-Order Models (ROMs) developed from 3D physics-based models for predicting transient thermal power output for an enhanced geothermal reservoir while explicitly accounting for…

Computational Engineering, Finance, and Science · Computer Science 2018-06-18 M. K. Mudunuru , S. Karra , D. R. Harp , G. D. Guthrie , H. S. Viswanathan

Many information systems employ lossy compression as a crucial intermediate stage among other processing components. While the important distortion is defined by the system's input and output signals, the compression usually ignores the…

Information Theory · Computer Science 2018-05-14 Yehuda Dar , Michael Elad , Alfred M. Bruckstein

We present a new hybrid semi-implicit finite volume / finite element numerical scheme for the solution of incompressible and weakly compressible media. From the continuum mechanics model proposed by Godunov, Peshkov and Romenski (GPR), we…

Numerical Analysis · Mathematics 2025-01-29 Saray Busto , Laura Río-Martín

In this paper, we propose a novel reduced order model (ROM) lengthscale that is constructed by using energy distribution arguments. The new energy-based ROM lengthscale is fundamentally different from the current ROM lengthscales, which are…

Numerical Analysis · Mathematics 2022-11-09 Changhong Mou , Elia Merzari , Omer San , Traian Iliescu

In this work we propose a novel method to ensure important entropy inequalities are satisfied semi-discretely when constructing reduced order models (ROMs) on nonlinear reduced manifolds. We are in particular interested in ROMs of systems…

Numerical Analysis · Mathematics 2024-07-18 Robin Klein , Benjamin Sanderse , Pedro Costa , Rene Pecnik , Ruud Henkes

We present a physical formulation, and a numerical algorithm, based on a class of general order parameters for simulating the motion of a mixture of $N$ ($N\geqslant 2$) immiscible incompressible fluids with given densities, dynamic…

Fluid Dynamics · Physics 2014-12-17 Suchuan Dong
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