English
Related papers

Related papers: Boundary layer stability analysis using the nonlin…

200 papers

Steady states and traveling waves play a fundamental role in understanding hydrodynamic problems. Even when unstable, these states provide the bifurcation-theoretic explanation for the origin of the observed states. In turbulent…

Fluid Dynamics · Physics 2018-05-08 Laurette S. Tuckerman , Jacob Langham , Ashley Willis

Exponential stabilization to time-dependent trajectories for the incompressible Navier-Stokes equations is achieved with explicit feedback controls. The fluid is contained in two-dimensional spatial domains and the control force is, at each…

Analysis of PDEs · Mathematics 2025-03-10 Sérgio S. Rodrigues , Dagmawi A. Seifu

In this work, we establish the convergence of 2D, stationary Navier-Stokes flows, $(u^\epsilon, v^\epsilon)$ to the classical Prandtl boundary layer, $(\bar{u}_p, \bar{v}_p)$, posed on the domain $(0, \infty) \times (0, \infty)$:…

Analysis of PDEs · Mathematics 2021-03-15 Sameer Iyer , Nader Masmoudi

Many spatial processes exhibit nonstationary features. We estimate a variance function from a single process observation where the errors are nonstationary and correlated. We propose a difference-based approach for a one-dimensional…

Methodology · Statistics 2016-05-24 Eunice J. Kim , Zhengyuan Zhu

We present a component-based model order reduction procedure to efficiently and accurately solve parameterized incompressible flows governed by the Navier-Stokes equations. Our approach leverages a non-overlapping optimization-based domain…

Numerical Analysis · Mathematics 2023-11-01 Tommaso Taddei , Xuejun Xu , Lei Zhang

We discuss the applicability of a unified hyperbolic model for continuum fluid and solid mechanics to modeling non-Newtonian flows and in particular to modeling the stress-driven solid-fluid transformations in flows of viscoplastic fluids,…

In the following paper we will consider Navier-Stokes problem and it's interpretation by hyperbolic waves, focusing on wave propagation. We will begin with solution for linear waves, then present problem for non-linear waves. Later we will…

Numerical Analysis · Computer Science 2016-01-22 Erik Arakelyan , Aram Serobyan , Narek Jilavyan

Achievement of solutions in Navier-Stokes equation is one of challenging quests, especially for its closure problem. For achievement of particular solutions, there are variety of numerical simulations including Direct Numerical Simulation…

Computational Physics · Physics 2018-11-13 Jinu Lee , Sangseung Lee , Donghyun You

Fourier Neural Operators (FNOs) have emerged as promising surrogates for partial differential equation solvers. In this work, we extensively tested FNOs on a variety of systems with non-linear and non-stationary properties, using a wide…

Computational Engineering, Finance, and Science · Computer Science 2025-11-13 Rad Haghi , Bipin Gaikwad , Abani Patra

This paper reviews results from the study of wall-bounded turbulent flows using statistical state dynamics (SSD) that demonstrate the benefits of adopting this perspective for understanding turbulence in wall-bounded shear flows. The SSD…

Fluid Dynamics · Physics 2017-02-10 Brian F. Farrell , Dennice F. Gayme , Petros J. Ioannou

Despite the physical importance, there are limited mathematical theories for the compressible Navier-Stokes equations with strong boundary layers. This is mainly due to the absence of a stream function structure, unlike the extensively…

Analysis of PDEs · Mathematics 2025-02-12 Shengxin Li , Tong Yang , Zhu Zhang

We propose Neural Walk-on-Spheres (NWoS), a novel neural PDE solver for the efficient solution of high-dimensional Poisson equations. Leveraging stochastic representations and Walk-on-Spheres methods, we develop novel losses for neural…

Machine Learning · Computer Science 2024-06-06 Hong Chul Nam , Julius Berner , Anima Anandkumar

We extend linear input/output (resolvent) analysis to take into account nonlinear triadic interactions by considering a finite number of harmonics in the frequency domain using the harmonic balance method. Forcing mechanisms that maximize…

Fluid Dynamics · Physics 2021-02-24 Georgios Rigas , Denis Sipp , Tim Colonius

Physics-informed neural networks (PINNs) are successful machine-learning methods for the solution and identification of partial differential equations (PDEs). We employ PINNs for solving the Reynolds-averaged Navier$\unicode{x2013}$Stokes…

Fluid Dynamics · Physics 2022-07-20 Hamidreza Eivazi , Mojtaba Tahani , Philipp Schlatter , Ricardo Vinuesa

Extending recent results in the isentropic case, we use a combination of asymptotic ODE estimates and numerical Evans-function computations to examine the spectral stability of shock-wave solutions of the compressible Navier--Stokes…

Mathematical Physics · Physics 2017-06-09 Jeffrey Humpherys , Gregory Lyng , Kevin Zumbrun

We study the existence and stability of non-trivial steady-state solutions to the two-dimensional incompressible Navier-Stokes equations in an annular domain $\Omega = B(0,b) \setminus \overline{B(0,a)}$ with radii $b>a>0$.The outer…

Analysis of PDEs · Mathematics 2025-08-12 Zhibo Hou , Liang Li , Quan Wang

Given a nonstationary trajectory of the Navier-Stokes system, a finite-dimensional feedback boundary controller stabilizing locally the system to the given trajectory is derived. Moreover the controller is supported in a given open subset…

Optimization and Control · Mathematics 2015-08-05 Sérgio S. Rodrigues

Building on work of Barker, Humpherys, Lafitte, Rudd, and Zumbrun in the shock wave case, we study stability of compressive, or "shock-like", boundary layers of the isentropic compressible Navier-Stokes equations with gamma-law pressure by…

Analysis of PDEs · Mathematics 2017-06-12 Nicola Costanzino , Jeffrey Humpherys , Toan Nguyen , Kevin Zumbrun

We present a simple and efficient variational finite difference method for simulating time-dependent Stokes flow in the presence of irregular free surfaces and moving solid boundaries. The method uses an embedded boundary approach on…

Computational Physics · Physics 2011-05-25 Christopher Batty , Robert Bridson

Many supervised machine learning methods have revolutionised the empirical modelling of complex systems. These empirical models, however, are usually "black boxes" and provide only limited physical explanations about the underlying systems.…