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We propose a new reduced order modeling strategy for tackling parametrized Partial Differential Equations (PDEs) with linear constraints, in particular Darcy flow systems in which the constraint is given by mass conservation. Our approach…

Numerical Analysis · Mathematics 2023-11-27 Wietse M. Boon , Nicola R. Franco , Alessio Fumagalli , Paolo Zunino

This work proposes a new stabilized $P_1\times P_0$ finite element method for solving the incompressible Navier--Stokes equations. The numerical scheme is based on a reduced Bernardi--Raugel element with statically condensed face bubbles…

Numerical Analysis · Mathematics 2023-04-06 Yuwen Li , Ludmil Zikatanov

Physical systems whose dynamics are governed by partial differential equations (PDEs) find applications in numerous fields, from engineering design to weather forecasting. The process of obtaining the solution from such PDEs may be…

Machine Learning · Computer Science 2022-09-21 Pratyush Bhatt , Yash Kumar , Azzeddine Soulaimani

Reduced-order models of time-dependent partial differential equations (PDEs) where the solution is assumed as a linear combination of prescribed modes are rooted in a well-developed theory. However, more general models where the reduced…

Analysis of PDEs · Mathematics 2021-09-30 William Anderson , Mohammad Farazmand

This paper extends a low-rank tensor decomposition (LRTD) reduced order model (ROM) methodology to simulate viscous flows and in particular to predict a smooth branch of solutions for the incompressible Navier-Stokes equations.…

Fluid Dynamics · Physics 2024-05-08 Maxim A. Olshanskii , Leo G. Rebholz

Structured on the paradigmatic Navier-Stokes flow model, we study a stochastically forced Taylor-Couette system in the narrow gap limit, in order to analyze the simultaneous impact of a non-conserved (Gaussian) force and a nonlinear…

Fluid Dynamics · Physics 2020-04-22 Larry E. Godwin , Sotos C. Generalis , Amit K. Chattopadhyay

Computational fluid dynamics (CFD) simulations play an important role in engineering science and applications, however, it is not applicable for problems requiring a large number of repeated calculations. Accordingly, many reduced-order…

Fluid Dynamics · Physics 2026-05-28 Shan Ding , Yongfu Tian , Rui Yang

The developments over the last five decades concerning numerical discretisations of the incompressible Navier--Stokes equations have lead to reliable tools for their approximation: those include stable methods to properly address the…

Numerical Analysis · Mathematics 2025-08-12 Dominic Breit , Andreas Prohl , Jörn Wichmann

This work introduces RedEigCD, the first self-adaptive timestepping technique specifically tailored for reduced-order models (ROMs) of the incompressible Navier-Stokes equations. Building upon linear stability concepts, the method adapts…

Numerical Analysis · Mathematics 2026-04-22 Josep Plana-Riu , Henrik Rosenberger , Benjamin Sanderse , F. Xavier Trias

Mathematical modeling of fluid dynamics for computer graphics requires high levels of theoretical rigor to ensure visually plausible and computationally efficient simulations. This paper presents an in-depth theoretical framework analyzing…

Fluid Dynamics · Physics 2024-11-05 Rômulo Damasclin Chaves dos Santos

Over the centuries mathematicians have been challenged by the partial differential equations (PDEs) that describe the motion of fluids in many physical contexts. Important and beautiful results were obtained in the past one hundred years,…

Analysis of PDEs · Mathematics 2023-07-05 Alexey Cheskidov , Mimi Dai , Susan Friedlander

The so-called 'direct' approach to separation of variables in linear PDEs is applied to the hydrodynamic stability problem. Calculations are made for the complete linear stability equations in cylindrical coordinates. Several classes of the…

Fluid Dynamics · Physics 2007-05-23 Georgy Burde , Alexander Zhalij

A model of fully developed turbulence of a compressible fluid is briefly reviewed. It is assumed that fluid dynamics is governed by a stochastic version of Navier-Stokes equation. We show how corresponding field theoretic-model can be…

Statistical Mechanics · Physics 2018-10-09 M. Hnatič , N. M. Gulitskiy , T. Lučivjanský , L. Mižišin , V. Škultéty

Unsteady fluid systems are nonlinear high-dimensional dynamical systems that may exhibit multiple complex phenomena both in time and space. Reduced Order Modeling (ROM) of fluid flows has been an active research topic in the recent decade…

Fluid Dynamics · Physics 2020-10-05 Hamidreza Eivazi , Hadi Veisi , Mohammad Hossein Naderi , Vahid Esfahanian

We develop an unsupervised machine learning algorithm for the automated discovery and identification of traveling waves in spatio-temporal systems governed by partial differential equations (PDEs). Our method uses sparse regression and…

Computational Physics · Physics 2020-05-20 Ariana Mendible , Steven L. Brunton , Aleksandr Y. Aravkin , Wes Lowrie , J. Nathan Kutz

New reduced-order models (ROMs) are derived for sinusoidal shear flow (also known as Waleffe flow) and plane Couette flow in small periodic domains. A first derivation for Waleffe flow exploits Fourier modes that form a natural orthonormal…

Fluid Dynamics · Physics 2021-04-07 André V. G. Cavalieri

This work investigates model reduction techniques for nonlinear parameterized and time-dependent PDEs, specifically focusing on bifurcating phenomena in Computational Fluid Dynamics (CFD). We develop interpretable and non-intrusive Reduced…

Numerical Analysis · Mathematics 2025-12-01 Lorenzo Tomada , Moaad Khamlich , Federico Pichi , Gianluigi Rozza

This paper introduces a Variational Multiscale Stabilization (VMS) formulation of the incompressible Navier--Stokes equations that utilizes the Finite Element Exterior Calculus (FEEC) framework. The FEEC framework preserves the geometric…

Numerical Analysis · Mathematics 2025-12-17 Kevin Dijkstra , Deepesh Toshniwal

In this paper, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements. We build on the fact that in a realistic application, there are…

Dynamical Systems · Mathematics 2020-06-01 Shady Ahmed , Suraj Pawar , Omer San , Adil Rasheed

The 3DVAR filter is prototypical of methods used to combine observed data with a dynamical system, online, in order to improve estimation of the state of the system. Such methods are used for high dimensional data assimilation problems,…

Probability · Mathematics 2015-06-11 D. Bloemker , K. J. H. Law , A. M. Stuart , K. C. Zygalakis