Comparing different nonlinear dimensionality reduction techniques for data-driven unsteady fluid flow modeling
Computational fluid dynamics (CFD) is known for producing high-dimensional
spatiotemporal data. Recent advances in machine learning (ML) have introduced a myriad …
spatiotemporal data. Recent advances in machine learning (ML) have introduced a myriad …
Proper orthogonal decomposition variational multiscale element free Galerkin (POD-VMEFG) meshless method for solving incompressible Navier–Stokes equation
M Dehghan, M Abbaszadeh - Computer Methods in Applied Mechanics …, 2016 - Elsevier
Recently, because of simplicity of meshless methods, they have been employed for solving
many partial differential equations. One of the meshless methods is element free Galerkin …
many partial differential equations. One of the meshless methods is element free Galerkin …
Calibration of POD reduced‐order models using Tikhonov regularization
In this paper we compare various methods of calibration that can be used in practice to
improve the accuracy of reduced‐order models based on proper orthogonal decomposition …
improve the accuracy of reduced‐order models based on proper orthogonal decomposition …
On closures for reduced order models—A spectrum of first-principle to machine-learned avenues
For over a century, reduced order models (ROMs) have been a fundamental discipline of
theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr …
theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr …
2D Burgers equation with large Reynolds number using POD/DEIM and calibration
Y Wang, IM Navon, X Wang… - International Journal for …, 2016 - Wiley Online Library
Model order reduction of the two‐dimensional Burgers equation is investigated. The
mathematical formulation of POD/discrete empirical interpolation method (DEIM)‐reduced …
mathematical formulation of POD/discrete empirical interpolation method (DEIM)‐reduced …
Identification strategies for model-based control
A reduced-order modelling (ROM) strategy is crucial to achieve model-based control in a
wide class of flow configurations. In turbulence, ROMs are mostly derived by Galerkin …
wide class of flow configurations. In turbulence, ROMs are mostly derived by Galerkin …
Low-dimensional characteristics of a transonic jet. Part 2. Estimate and far-field prediction
Complementary low-dimensional techniques are modified to estimate the most energetic
turbulent features of a Mach 0.85 axisymmetric jet in the flow's near-field regions via spectral …
turbulent features of a Mach 0.85 axisymmetric jet in the flow's near-field regions via spectral …
Data-driven modeling of transonic unsteady flows and efficient analysis of fluid–structure stability
The reduced-order aerodynamic models constructed via the linear/nonlinear system
identification methodologies cannot reveal the flow characteristics of the fluid–structure …
identification methodologies cannot reveal the flow characteristics of the fluid–structure …
Spiral flow instability between a rotor and a stator in high-speed turbomachinery and its relation to fan noise
T Suzuki - Journal of Fluid Mechanics, 2023 - cambridge.org
Hydrodynamic instabilities in the interstage of turbomachinery and their relation to fan
broadband noise are investigated over wide operating conditions. By applying compressible …
broadband noise are investigated over wide operating conditions. By applying compressible …
Linear reduced-order model based on PIV data of flow field around airfoil
K Nankai, Y Ozawa, T Nonomura… - Transactions of the Japan …, 2019 - jstage.jst.go.jp
In this study, a linear reduced-order model of flow fields around a NACA0015 is constructed
based on time-resolved particle image velocimetry (PIV) data. The PIV data were obtained at …
based on time-resolved particle image velocimetry (PIV) data. The PIV data were obtained at …