Data-driven modeling for unsteady aerodynamics and aeroelasticity

J Kou, W Zhang - Progress in Aerospace Sciences, 2021 - Elsevier
Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

[HTML][HTML] Improving aircraft performance using machine learning: A review

S Le Clainche, E Ferrer, S Gibson, E Cross… - Aerospace Science and …, 2023 - Elsevier
This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …

Data-driven modal decomposition methods as feature detection techniques for flow problems: A critical assessment

B Begiashvili, N Groun, J Garicano-Mena… - Physics of …, 2023 - pubs.aip.org
Modal decomposition techniques are showing a fast growth in popularity for their wide range
of applications and their various properties, especially as data-driven tools. There are many …

Koopman analysis by the dynamic mode decomposition in wind engineering

CY Li, Z Chen, X Zhang, KT Tim, C Lin - Journal of Wind Engineering and …, 2023 - Elsevier
The Koopman theory, a concept to globally model nonlinear signals by a linear Hamiltonian,
has been at the frontier of fluid mechanics research for the last decade. Wind engineering …

The linear-time-invariance notion to the Koopman analysis: The architecture, pedagogical rendering, and fluid–structure association

CY Li, Z Chen, X Lin, AU Weerasuriya, X Zhang… - Physics of …, 2022 - pubs.aip.org
This work augments a Linear-Time-Invariance (LTI) notion to the Koopman analysis, finding
an invariant subspace on which consistent Koopman modes are expanded with fluid …

[HTML][HTML] A parametric and feasibility study for data sampling of the dynamic mode decomposition: Spectral insights and further explorations

CY Li, Z Chen, TKT Tse, AU Weerasuriya, X Zhang… - Physics of …, 2022 - pubs.aip.org
The present work extends the parametric investigation on the sampling nuances of dynamic
mode decomposition (DMD) under Koopman analysis. Through turbulent wakes, the study …

The linear-time-invariance notion of the Koopman analysis. Part 2. Dynamic Koopman modes, physics interpretations and phenomenological analysis of the prism …

CY Li, Z Chen, KT Tim, AU Weerasuriya… - Journal of Fluid …, 2023 - cambridge.org
This serial work presents a linear-time-invariance (LTI) notion to the Koopman analysis,
finding consistent and physically meaningful Koopman modes and addressing a long …

Higher order dynamic mode decomposition: From fluid dynamics to heart disease analysis

N Groun, M Villalba-Orero, E Lara-Pezzi… - Computers in Biology …, 2022 - Elsevier
In this work, we study in detail the performance of Higher Order Dynamic Mode
Decomposition (HODMD) technique when applied to echocardiography images. HODMD is …

Suppression of vortex shedding using a slit through the circular cylinder at low Reynolds number

A Mishra, A De - European Journal of Mechanics-B/Fluids, 2021 - Elsevier
The present article aims to study the suppression of vortex shedding using a passive flow
control technique (slit through a circular cylinder) in the laminar regime (Re= 100–500). The …

[HTML][HTML] A dynamic mode decomposition technique for the analysis of non–uniformly sampled flow data

B Li, J Garicano-Mena, E Valero - Journal of Computational Physics, 2022 - Elsevier
Abstract A novel Dynamic Mode Decomposition (DMD) technique capable of handling non–
uniformly sampled data is proposed. As it is usual in DMD analysis, a linear relationship …