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The theory of transient growth describes how linear mechanisms can cause temporary amplification of disturbances even when the linearized system is asymptotically stable as defined by its eigenvalues. This growth is traditionally quantified…

Fluid Dynamics · Physics 2023-02-23 Peter Frame , Aaron Towne

We develop a perturbation-based frequency-response framework for analyzing amplification mechanisms that are central to subcritical routes to transition in wall-bounded shear flows. By systematically expanding the input-output dynamics of…

Fluid Dynamics · Physics 2026-05-04 Dušan Božić , Anubhav Dwivedi , Mihailo R. Jovanović

We consider a class of learning problems that involve a structured sparsity-inducing norm defined as the sum of $\ell_\infty$-norms over groups of variables. Whereas a lot of effort has been put in developing fast optimization methods when…

Machine Learning · Computer Science 2010-09-02 Julien Mairal , Rodolphe Jenatton , Guillaume Obozinski , Francis Bach

We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on…

Dynamical Systems · Mathematics 2017-11-22 Piyush Grover , Karthik Elamvazhuthi

The transient growth of disturbances made possible by the non-normality of the linearized Navier-Stokes equations plays an important role in bypass transition for many shear flows. Transient growth is typically quantified by the maximum…

Fluid Dynamics · Physics 2026-03-24 Zhicheng Kai , Peter Frame , Aaron Towne

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

We discuss how searching for finite amplitude disturbances of a given energy which maximise their subsequent energy growth after a certain later time $T$ can be used to probe phase space around a reference state and ultimately to find other…

Fluid Dynamics · Physics 2017-08-23 Daniel Olvera , Rich R. Kerswell

Prior modal stability analysis (Kojima et al., Phys. Fluids, vol. 27, 1984) predicted that a rising or sedimenting droplet in a viscous fluid is stable in the presence of surface tension no matter how small, in contrast to experimental and…

Fluid Dynamics · Physics 2015-12-01 Giacomo Gallino , Lailai Zhu , Francois Gallaire

We investigate here linear stability in a canonical three-dimensional boundary layer generated by the superposition of a spanwise pressure gradient upon an otherwise standard channel flow. As the main result, we introduce a simple…

Fluid Dynamics · Physics 2024-06-28 Muhammad Abdullah

In this paper, we propose a sparsity-promoting feedback control design for stochastic linear systems with multiplicative noise. The objective is to identify a sparse control architecture that optimizes the closed-loop performance while…

Optimization and Control · Mathematics 2022-08-22 Yi Guo , Ognjen Stanojev , Gabriela Hug , Tyler Summers

This article introduces, and reviews recent work using, a simple optimisation technique for analysing the nonlinear stability of a state in a dynamical system. The technique can be used to identify the most efficient way to disturb a system…

Fluid Dynamics · Physics 2014-08-18 R. R. Kerswell , C. C. T. Pringle , A. P. Willis

We propose a novel stability criterion for incompressible shear flows by combining input-output analysis and the small-gain theorem. The criterion yields an explicit threshold on the magnitude of velocity perturbations about a given base…

Fluid Dynamics · Physics 2026-03-04 Ofek Frank-Shapir , Igal Gluzman

We study gravitationally unstable, transient, diffusive boundary layers in porous media using modal and nonmodal stability methods. Using nonmodal stability theory, we demonstrate that both the onset of linear instabilities and the shape of…

Fluid Dynamics · Physics 2019-03-05 Don Daniel , Nils Tilton , Amir Riaz

Existing methods to determine the stability of a power system to small perturbations are based on eigenvalue analysis and focus on the asymptotic (long-term) behavior of the power grid. During the preasymptotic (short-term) transient,…

Optimization and Control · Mathematics 2023-02-22 Daniel Adrian Maldonado , Emil Constantinescu , Junbo Zhao , Mihai Anitescu

Nonmodal transient growth studies and estimation of optimal perturbations have been made for the compressible plane Couette flow with three-dimensional disturbances. The maximum amplification of perturbation energy over time, $G_{\max}$, is…

Fluid Dynamics · Physics 2009-11-13 M. Malik , Meheboob Alam , J. Dey

In this article we propose a scalable shape optimization algorithm which is tailored for large scale problems and geometries represented by hierarchically refined meshes. Weak scalability and grid independent convergence is achieved via a…

Optimization and Control · Mathematics 2022-05-09 Jose Pinzon , Martin Siebenborn

This paper treats the problem of minimizing a general continuously differentiable function subject to sparsity constraints. We present and analyze several different optimality criteria which are based on the notions of stationarity and…

Information Theory · Computer Science 2012-03-22 Amir Beck , Yonina C. Eldar

This work proposes a method to identify and isolate the physical mechanisms that are responsible for linear energy amplification in fluid flows. This is achieved by applying a sparsity-promoting methodology to the resolvent form of the…

Fluid Dynamics · Physics 2025-04-17 Scott T. M. Dawson , Jaime Prado Zayas , Barbara Lopez-Doriga

We investigate the energy transfer from the mean profile to velocity fluctuations in channel flow by calculating nonlinear optimal disturbances,i.e. the initial condition of a given finite energy that achieves the highest possible energy…

Fluid Dynamics · Physics 2025-06-25 Dario Klingenberg , Rich R. Kerswell

We present the framework of slowly varying regression under sparsity, allowing sparse regression models to exhibit slow and sparse variations. The problem of parameter estimation is formulated as a mixed-integer optimization problem. We…

Machine Learning · Computer Science 2023-11-14 Dimitris Bertsimas , Vassilis Digalakis , Michael Linghzi Li , Omar Skali Lami