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The conceptual picture underlying resolvent analysis(RA) is that the nonlinear term in the Navier-Stokes(NS) equations provides an intrinsic forcing to the linear dynamics, a description inspired by control theory. The inverse of the linear…

Fluid Dynamics · Physics 2021-09-28 Benedikt Barthel , Salvador Gomez , Beverley McKeon

The interaction between shear driven turbulence and stratification is a key process in a wide array of geophysical flows with spatio-temporal scales that span many orders of magnitude. A quick numerical model prediction based on external…

Fluid Dynamics · Physics 2021-08-18 M. A. Ahmed , H. J. Bae , A. F. Thompson , B. J. McKeon

The quadratic convection term in the incompressible Navier-Stokes equations is considered as a nonlinear forcing to the linear resolvent operator, and it is studied in the Fourier domain through the analysis of interactions between…

Fluid Dynamics · Physics 2025-03-11 Yuting Huang , Simon S. Toedtli , Gregory P. Chini , Beverley J. McKeon

The ability of linear stochastic response analysis to estimate coherent motions is investigated in turbulent channel flow at friction Reynolds number Re$_\tau$ = 1007. The analysis is performed for spatial scales characteristic of…

Fluid Dynamics · Physics 2021-02-02 Pierluigi Morra , Onofrio Semeraro , Dan S. Henningson , Carlo Cossu

We combine resolvent-mode decomposition with techniques from convex optimization to optimally approximate velocity spectra in a turbulent channel. The velocity is expressed as a weighted sum of resolvent modes that are dynamically…

Fluid Dynamics · Physics 2014-05-22 R. Moarref , M. R. Jovanovic , J. A. Tropp , A. S. Sharma , B. J. McKeon

Direct numerical simulations, performed with a high-order spectral-element method, are used to study coherent structures in turbulent pipe flow at friction Reynolds numbers $Re_{\tau} = 180$ and $550$. The database was analysed using…

Fluid Dynamics · Physics 2023-07-19 Leandra Abreu , André Cavalieri , Philipp Schlatter , Ricardo Vinuesa , Dan Henningson

We reconstruct the velocity field of incompressible flows given a finite set of measurements. For the spatial approximation, we introduce the Sparse Fourier divergence-free (SFdf) approximation based on a discrete $L^2$ projection. Within…

Fluid Dynamics · Physics 2021-10-13 Luis Espath , Dmitry Kabanov , Jonas Kiessling , Raúl Tempone

Stochastic linear modelling proposed in Tissot, M\'emin & Cavalieri (J. Fluid Mech., vol. 912, 2021, A51) is based on classical conservation laws subject to a stochastic transport. Once linearised around the mean flow and expressed in the…

Fluid Dynamics · Physics 2022-07-27 Gilles Tissot , André Cavalieri , Etienne Mémin

An analysis of the statistics of the non-linear terms in resolvent analysis is performed in this work for turbulent Couette flow at low Reynolds number. Data from a direct numerical simulation of a minimal flow unit, at Reynolds number 400,…

We construct a local in time spatially real-analytic solution to the 2D and 3D stochastic Navier--Stokes equation driven by a spatially real-analytic multiplicative and transport noise but emanating from an initial condition that is only…

Analysis of PDEs · Mathematics 2024-07-15 Dan Crisan , Prince Romeo Mensah

We propose and study a temporal, and spatio-temporal discretisation of the 2D stochastic Navier--Stokes equations in bounded domains supplemented with no-slip boundary conditions. Considering additive noise, we base its construction on the…

Numerical Analysis · Mathematics 2022-03-23 Dominic Breit , Andreas Prohl

Linearisation of the Navier-Stokes equations about the mean of a turbulent flow forms the foundation of popular models for energy amplification and coherent structures, including resolvent analysis. While the Navier-Stokes equations can be…

We employ a resolvent-based methodology to estimate velocity and pressure fluctuations within turbulent channel flows at friction Reynolds numbers of approximately 180, 550 and 1000 using measurements of shear stress and pressure at the…

Fluid Dynamics · Physics 2021-10-04 Filipe R. Amaral , André V. G. Cavalieri , Eduardo Martini , Peter Jordan , Aaron Towne

Four different applications of spectral proper orthogonal decomposition (SPOD): low-rank reconstruction, denoising, frequency-time analysis, and prewhitening are demonstrated on large-eddy simulation data of a turbulent jet. SPOD-based…

Fluid Dynamics · Physics 2021-09-22 Akhil Nekkanti , Oliver T. Schmidt

The resolvent analysis reveals the worst-case disturbances and the most amplified response in a fluid flow that can develop around a stationary base state. The recent work by Padovan et al.(2020) extended the classical resolvent analysis to…

Fluid Dynamics · Physics 2024-12-16 Md Rashidul Islam , Yiyang Sun

We propose a novel framework for approximating the statistical properties of turbulent flows by combining variational methods for the search of unstable periodic orbits with resolvent analysis for dimensionality reduction. Traditional…

Chaotic Dynamics · Physics 2025-01-22 Thomas Burton , Sean Symon , Ati Sharma , Davide Lasagna

We study the three-dimensional hyper-dissipative Navier-Stokes system in the near-critical regime below the Lions threshold. Leveraging a quantified analyticity-sparseness gap, we introduce a time-weighted bridge inequality across…

Analysis of PDEs · Mathematics 2025-12-04 Moses Patson Phiri

Consider the resolvent problem associated with the linearized viscous flow around a rotating body. Within a setting of classical Sobolev spaces, this problem is not well posed on the whole imaginary axis. Therefore, a framework of…

Analysis of PDEs · Mathematics 2022-05-04 Thomas Eiter

An analytical framework for studying the logarithmic region of turbulent channels is formulated. We build on recent findings (Moarref et al., J. Fluid Mech., 734, 2013) that the velocity fluctuations in the logarithmic region can be…

Fluid Dynamics · Physics 2014-09-23 Rashad Moarref , Ati S. Sharma , Joel A. Tropp , Beverley J. McKeon

Sparsity-based methods are widely used in machine learning, statistics, and signal processing. There is now a rich class of structured sparsity approaches that expand the modeling power of the sparsity paradigm and incorporate constraints…

Data Structures and Algorithms · Computer Science 2017-12-22 Aleksander Mądry , Slobodan Mitrović , Ludwig Schmidt