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This paper addresses the boundary stabilization of a flexible wing model, both in bending and twisting displacements, under unsteady aerodynamic loads, and in presence of a store. The wing dynamics is captured by a distributed parameter…

Optimization and Control · Mathematics 2018-08-29 Hugo Lhachemi , David Saussié , Guchuan Zhu

The destruction of a chaotic attractor leading to rough changes in the dynamics of a dynamical system is studied. Local bifurcations are characterised by a single or a pair of characteristic exponents crossing the imaginary axis. The…

Chaotic Dynamics · Physics 2020-11-16 Alexis Tantet , Valerio Lucarini , Frank Lunkeit , Henk A. Dijkstra

This study focuses on the numerical simulation of high Reynolds number separated flows and proposes a data-driven approach to improve the predictive capability of the SA turbulence model. First, data assimilation was performed on two…

Fluid Dynamics · Physics 2025-03-13 Xuxiang Sun , Xianglin Shan , Yilang Liu , Weiwei Zhang

We investigate the unsteady lift response of compliant membrane wings in hovering kinematics by combining analytical inviscid theory with experimental results. An unsteady aerodynamic model is derived for a compliant thin aerofoil immersed…

Fluid Dynamics · Physics 2026-01-14 Sonya Tiomkin , Alexander Gehrke

The stratified inclined duct (SID) sustains an exchange flow in a long, gently sloping duct as a model for continuously-forced density-stratified flows such as those found in estuaries. Experiments have shown that the emergence of…

Airfoil aerodynamic optimization based on single-point design may lead to poor off-design behaviors. Multipoint optimization that considers the off-design flow conditions is usually applied to improve the robustness and expand the flight…

Fluid Dynamics · Physics 2022-09-21 Yunjia Yang , Runze Li , Yufei Zhang , Haixin Chen

The tendency of a jet to stay attached to a flat or convex surface is called the Coand\u{a} effect and has many potential technical applications. The aim of this thesis is to assess how well Computational Fluid Dynamics can capture it. A…

Computational Engineering, Finance, and Science · Computer Science 2021-10-06 Florent Mauret

We study of the formation of pattern-forming fronts in the presence of a rigidly-propagating parameter ramp which is slowly-varying in space. In the context of the prototypical supercritical complex Ginzburg-Landau equation, we show that…

Pattern Formation and Solitons · Physics 2026-05-26 Ryan Goh , Benjamin Krewson , Nilay Patel , Kiersten Ratcliff

We examine a model system where attractors may consist of a heteroclinic cycle between chaotic sets; this `cycling chaos' manifests itself as trajectories that spend increasingly long periods lingering near chaotic invariant sets…

chao-dyn · Physics 2009-10-28 Peter Ashwin , A. M. Rucklidge

Model reduction of high-dimensional dynamical systems alleviates computational burdens faced in various tasks from design optimization to model predictive control. One popular model reduction approach is based on projecting the governing…

Dynamical Systems · Mathematics 2018-08-24 Francisco J. Gonzalez , Maciej Balajewicz

In order to obtain the information about flow field, traditional computational fluid dynamics methods need to solve the Navier-Stokes equations on the mesh with boundary conditions, which is a time-consuming task. In this work, a…

Fluid Dynamics · Physics 2022-07-05 Kuijun Zuo , Shuhui Bu , Weiwei Zhang , Jiawei Hu , Zhengyin Ye , Xianxu Yuan

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

We present a novel method for learning reduced-order models of dynamical systems using nonlinear manifolds. First, we learn the manifold by identifying nonlinear structure in the data through a general representation learning problem. The…

Numerical Analysis · Mathematics 2026-05-27 Rudy Geelen , Laura Balzano , Stephen Wright , Karen Willcox

This paper focuses on addressing challenges posed by non-homogeneous unstructured grids, commonly used in Computational Fluid Dynamics (CFD). Their prevalence in CFD scenarios has motivated the exploration of innovative approaches for…

Computational Engineering, Finance, and Science · Computer Science 2024-05-08 Gabriele Immordino , Andrea Vaiuso , Andrea Da Ronch , Marcello Righi

The uncertainty associated with the experimental inflow in a wind tunnel affects the prediction of the flow of interest by numerical simulations. We evaluate this impact using uncertainty quantification. A method is developed and applied to…

Fluid Dynamics · Physics 2021-04-14 Nicola Detomaso , Vincent Brion , Julien Dandois , Marie Couliou , Éric Savin

Laminar drag reduction is a critical technology for enhancing the endurance and station-keeping capabilities of airship platforms. However, existing transport-based transition models fail to account for the premature transition induced by…

Fluid Dynamics · Physics 2026-03-04 Yayun Shi , Qiyun Wang , Xiaosong Lan , Bo Wang , Tihao Yang , Yifu Chen

Spanwise wall forcing in the form of streamwise-travelling waves is applied to the suction side of a transonic airfoil with a shock wave to reduce aerodynamic drag. The study, conducted using direct numerical simulations, extends earlier…

Fluid Dynamics · Physics 2025-02-10 Niccolò Berizzi , Davide Gatti , Giulio Soldati , Sergio Pirozzoli , Maurizio Quadrio

A subcritical pattern-forming system with nonlinear advection in a bounded domain is recast as a slow-fast system in space and studied using a combination of geometric singular perturbation theory and numerical continuation. Two types of…

Pattern Formation and Solitons · Physics 2018-03-20 Daniele Avitabile , Mathieu Desroches , Edgar Knobloch , Martin Krupa

Data-driven reduced-order models of the dynamics of complex flows are important for tasks related to design, understanding, prediction, and control. Many flows obey symmetries, and the present work illustrates how these can be exploited to…

Machine Learning · Computer Science 2025-04-23 Carlos E. Pérez De Jesús , Alec J. Linot , Michael D. Graham

Triadic interactions are the fundamental mechanism of energy transfer in fluid flows. This work introduces bispectral mode decomposition as a direct means of educing flow structures that are associated with triadic interactions from…

Fluid Dynamics · Physics 2021-01-20 Oliver T. Schmidt