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This paper considers the problem of designing a continuous-time dynamical system that solves a constrained nonlinear optimization problem and makes the feasible set forward invariant and asymptotically stable. The invariance of the feasible…

Optimization and Control · Mathematics 2024-08-27 Ahmed Allibhoy , Jorge Cortés

Adjoint-based sensitivity analysis is of interest in computational science due to its ability to compute sensitivities at a lower cost with respect to several design parameters. However, conventional sensitivity analysis methods fail in the…

Numerical Analysis · Mathematics 2025-07-15 Pranshul Thakur , Siva Nadarajah

We discuss the application of the resolvent technique to prove stability of plane Couette flow. Using this technique, we derive a threshold amplitude for perturbations that can lead to turbulence in terms of the Reynolds number. Our main…

Analysis of PDEs · Mathematics 2016-09-07 Pablo Braz e Silva

In this study, new turbulence closure equations are derived in the light of turbulence as a continuous phase transition phenomenon. Closed-form Reynolds averaged Navier-Stokes equations due to those closure equations are solved numerically…

Fluid Dynamics · Physics 2026-04-22 Mohammed A. Azim

In this paper, we propose an approach for simulating wall-bounded incompressible turbulent flows by integrating the technology of random vortex method with the core principles of large-eddy simulations (LES). In particular, we employ the…

Fluid Dynamics · Physics 2025-11-11 Zihao Guo , Zhongmin Qian

We propose a framework for developing wall models for large-eddy simulation that is able to capture pressure-gradient effects using multi-agent reinforcement learning. Within this framework, the distributed reinforcement learning agents…

Fluid Dynamics · Physics 2024-07-29 Di Zhou , H. Jane Bae

In view of solving convex optimization problems with noisy gradient input, we analyze the asymptotic behavior of gradient-like flows under stochastic disturbances. Specifically, we focus on the widely studied class of mirror descent schemes…

Optimization and Control · Mathematics 2017-09-21 Panayotis Mertikopoulos , Mathias Staudigl

Designing effective optimisation strategies for unsteady flows in the presence of complex dynamics is challenging. Gradient-based optimisation algorithms that rely on gradient information obtained from adjoint equations are efficient for…

In this paper, we present the results of a numerical study of air-water turbulent bubbly flow in a periodic vertical square duct. The study is conducted using a novel numerical technique which leverages Volume of Fluid method for interface…

Fluid Dynamics · Physics 2022-12-27 Purushotam Kumar , Surya Pratap Vanka

In this paper, we propose novel algorithms integrated projection-free techniques with accelerated gradient flows to minimize bending energies for nonlinear plates with non-convex metric constraints. We discuss the stability and constraint…

Numerical Analysis · Mathematics 2025-06-18 Guozhi Dong , Hailong Guo , Shuo Yang

It is well-known that linearized perturbation methods for sensitivity analysis, such as tangent or adjoint equation-based, finite difference and automatic differentiation are not suitable for turbulent flows. The reason is that turbulent…

Chaotic Dynamics · Physics 2019-07-04 Nisha Chandramoorthy , Qiqi Wang

The present work compares results for different numerical methods in search of alternatives to improve the quality of large-eddy simulations for the problem of supersonic turbulent jet flows. Previous work has analyzed supersonic jet flows…

Fluid Dynamics · Physics 2025-09-23 D. F. Abreu , C. Junqueira-Junior , E. T. V. Dauricio , J. L. F. Azevedo

Many large-scale and distributed optimization problems can be brought into a composite form in which the objective function is given by the sum of a smooth term and a nonsmooth regularizer. Such problems can be solved via a proximal…

Optimization and Control · Mathematics 2020-06-26 Sepideh Hassan-Moghaddam , Mihailo R. Jovanović

This paper addresses the problem of obtaining low-order models of fluid flows for the purpose of designing robust feedback controllers. This is challenging since whilst many flows are governed by a set of nonlinear, partial…

Large eddy approximation of turbulent flow is given a natural setting within the DSC framework of computational fluid dynamics. Periodic cellular coarse-graining prevents the nodal flow from piling up and preserves its large patterns. The…

Numerical Analysis · Mathematics 2008-08-28 Steffen Hein

Aerial operation in turbulent environments is a challenging problem due to the chaotic behavior of the flow. This problem is made even more complex when a team of aerial robots is trying to achieve coordinated motion in turbulent wind…

Robotics · Computer Science 2023-06-09 Diego Patiño , Siddharth Mayya , Juan Calderon , Kostas Daniilidis , David Saldaña

Opposition flow control is a robust strategy that has been proved effective in turbulent wall-bounded flows. Its conventional setup consists of measuring wall-normal velocity in the buffer layer and opposing it at the wall. This work…

Fluid Dynamics · Physics 2022-02-16 Anna Guseva , Javier Jimenez

Over the last two decades, both experiments and simulations have demonstrated that transverse wall oscillations with properly selected amplitude and frequency can reduce turbulent drag by as much as 40%. In this paper, we develop a…

Fluid Dynamics · Physics 2013-04-23 Rashad Moarref , Mihailo R. Jovanović

Coarse resolution numerical ocean models must typically include a parameterisation for mesoscale turbulence. A common recipe for such parameterisations is to invoke down-gradient mixing, or diffusion, of some tracer quantity, such as…

Fluid Dynamics · Physics 2016-08-03 Julian Mak , James R. Maddison , David P. Marshall

A cylindrical and inclined jet in crossflow is studied under two distinct velocity ratios, $r=1$ and $r=2$, using highly resolved large eddy simulations (LES). First, an investigation of turbulent scalar mixing sheds light onto the…

Fluid Dynamics · Physics 2020-12-30 Pedro M. Milani , Julia Ling , John K. Eaton