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Related papers: Estimating flow fields with Reduced Order Models

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In this paper, a reduced-order model (ROM) based on the proper orthogonal decomposition and the discrete empirical interpolation method is proposed for efficiently simulating time-fractional partial differential equations (TFPDEs). Both…

Numerical Analysis · Mathematics 2024-02-07 Hongfei Fu , Hong Wang , Zhu Wang

In this paper, we develop data-driven closure/correction terms to increase the pressure and velocity accuracy of reduced order models (ROMs) for fluid flows. Specifically, we propose the first pressure-based data-driven variational…

Numerical Analysis · Mathematics 2023-01-25 Anna Ivagnes , Giovanni Stabile , Andrea Mola , Traian Iliescu , Gianluigi Rozza

The numerical simulation of incompressible flows is challenging due to the tight coupling of velocity and pressure. Projection methods offer an effective solution by decoupling these variables, making them suitable for large-scale…

Numerical Analysis · Mathematics 2025-12-12 Mejdi Azaïez , Yayu Guo , Carlos Núñez Fernández , Samuele Rubino , Chuanju Xu

The paper presents a Projection-Based Reduced-Order Model for simulations of high Reynolds turbulent flows. The PBROM are enhanced by incorporating various models of turbulent viscosity and residual closures to model the effects of…

Computational Engineering, Finance, and Science · Computer Science 2021-05-25 My Ha Dao , Hoang Huy Nguyen

Reduced-order models (ROMs) of turbulent flows based on Galerkin projection often require many degrees of freedom to resolve the dynamics of the turbulence, or simulation data to obtain an optimal modal basis. However, obtaining simulation…

Fluid Dynamics · Physics 2025-11-21 Ian Addison-Smith , Igor A. Maia , Benjamin Herrmann , Andre V. G. Cavalieri

This study concerns the development of a data-based compact model for the prediction of the fluid temperature evolution in district heating (DH) pipeline networks. This so-called "reduced-order model" (ROM) is obtained from reduction of the…

Numerical Analysis · Mathematics 2022-11-28 Mengting Jiang , Michel Speetjens , Camilo Rindt , David Smeulders

Cardio-mechanical models can be used to support clinical decision-making. Unfortunately, the substantial computational effort involved in many cardiac models hinders their application in the clinic, despite the fact that they may provide…

Computational Engineering, Finance, and Science · Computer Science 2026-05-19 Robin Willems , Peter Förster , Sebastian Schöps , Olaf van der Sluis , Clemens V. Verhoosel

Spatial filtering has been central in the development of large eddy simulation reduced order models (LES-ROMs) and regularized reduced order models (Reg-ROMs), In this paper, we perform a numerical investigation of spatial filtering. To…

Numerical Analysis · Mathematics 2017-07-14 L. C. Berselli , D. Wells , X. Xie , T. Iliescu

Reduced order methods (ROMs) for the incompressible Navier--Stokes equations, based on proper orthogonal decomposition (POD), are studied that include snapshots which approach the temporal derivative of the velocity from a full order mixed…

Numerical Analysis · Mathematics 2023-04-18 Bosco García-Archilla , Volker John , Sarah Katz , Julia Novo

In transonic turbine stages, complex interactions between trailing edge shocks from nozzle guide vanes and rotor blades generate unsteady wall pressure fields, impacting rotor aerodynamic performance and structural integrity. While…

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations, in which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space has a small Kolmogorov…

Numerical Analysis · Mathematics 2020-11-17 Youngkyu Kim , Youngsoo Choi , David Widemann , Tarek Zohdi

Reduced order modeling (ROM) provides an efficient framework to compute solutions of parametric problems. Basically, it exploits a set of precomputed high-fidelity solutions --- computed for properly chosen parameters, using a full-order…

Numerical Analysis · Mathematics 2019-11-19 Nicola Demo , Marco Tezzele , Gianluigi Rozza

This paper presents a novel, more efficient proper orthogonal decomposition (POD) based reduced-order model (ROM) for compressible flows. In this POD model the governing equations, i.e., the conservation of mass, momentum, and energy…

Computational Physics · Physics 2021-02-03 Elizabeth H. Krath , Forrest L. Carpenter , Paul G. A. Cizmas , David A. Johnston

Forecasting atmospheric flows with traditional discretization methods, also called full order methods (e.g., finite element methods or finite volume methods), is computationally expensive. We propose to reduce the computational cost with a…

Numerical Analysis · Mathematics 2025-04-03 Arash Hajisharifi , Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

The impact of chemical reactions on the robustness and accuracy of projection-based Reduced-Order Models (ROMs) of fluid flows is investigated. Both Galerkin and Least-Squares Petrov Galerkin ROMs are shown to be less robust in reacting…

Computational Physics · Physics 2019-07-19 Cheng Huang , Karthik Duraisamy , Charles L. Merkle

In this paper, we propose a new stabilized projection-based POD-ROM for the numerical simulation of incompressible flows. The new method draws inspiration from successful numerical stabilization techniques used in the context of Finite…

Numerical Analysis · Mathematics 2019-07-23 Samuele Rubino

Reduced-order models (ROMs) are often used to accelerate the simulation of large physical systems. However, traditional ROM techniques, such as those based on proper orthogonal decomposition (POD), often struggle with advection-dominated…

Numerical Analysis · Mathematics 2025-11-07 Toby van Gastelen , Wouter Edeling , Benjamin Sanderse

The flow behavior in the continuous casting tundish plays a critical role in steel quality and is typically characterized via residence time distribution (RTD) curves. This study investigates the fluid flow behaviour in a single-strand…

Proper-orthogonal decomposition (POD) based reduced-order models (ROM) of structurally dominant fluid flow can support a wide range of engineering applications. Yet, although they perform well for unsteady laminar flows, their…

Fluid Dynamics · Physics 2025-03-11 Haroon Imtiaz , Imran Akhtar , Muhammad R. Hajj

Water networks are used in numerous applications, all of which have the essential task of real-time monitoring and control of water states. A framework for the generation of efficient models of water networks suitable for real-time…

Systems and Control · Electrical Eng. & Systems 2022-03-23 Ahmed Elkhashap , Daniel Rüschen , Dirk Abel