Analysis of time-resolved PIV measurements of a confined turbulent jet using POD and Koopman modes

Semeraro, Onofrio; Bellani, Gabriele; Lundell, Fredrik

doi:10.1007/s00348-012-1354-9

Cited by 124 publications

(51 citation statements)

References 23 publications

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“…These calculated values show good agreement with the values obtained from the v spectra at the PIV probe location ( Figure 5), giving cofidence in the presented frequencies. Additional analysis is carried out on the temporal coefficients of the POD modes as they represent the temporal signature of the mode (Semeraro et al, 2012;Meyer et al, 2007). This helps to link the corresponding mode 4 with f 0 and mode 2 with f 0−1/2 , as the identified frequencies in the v spectra.…”

Section: Flow Fieldmentioning

confidence: 99%

Upstream shear-layer stabilisation via self-oscillating trailing edge flaplets

Talboys

Brücker

2018

Exp Fluids

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This is the published version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThe flow around a symmetric aerofoil (NACA 0012) with an array of flexible flaplets attached to the trailing edge has been investigated at Reynolds numbers of 100,000-150,000 using high-speed time-resolved particle image velocimetry (HS TR-PIV) and motion tracking of the flaplets' tips. Particular attention has been made on the upstream effect on the boundary layer evolution along the suction side of the wing, at angles of attack of 0 • and 10• . For the plain aerofoil, without flaplets, the boundary layer on the second half of the aerofoil shows the formation of rollers as the shear-layer rolls-up in the fundamental instability mode (linear state). Proper orthogonal decomposition analysis shows that non-linear modes are also present, the most dominant being the pairing of successive rollers. When the flaplets are attached, it is shown that the flow-induced oscillations of the flaplets are able to create a lock-in effect that stabilises the linear state of the shear layer, whilst delaying or damping the growth of non-linear modes. It is hypothesised that the modified trailing edge is beneficial for reducing drag and can reduce aeroacoustic noise production in the lower frequency band, as indicated by an initial acoustic investigation. List of symbols

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Section: Flow Fieldmentioning

confidence: 99%

Upstream shear-layer stabilisation via self-oscillating trailing edge flaplets

Talboys

Brücker

2018

Exp Fluids

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“…The temporal mode a 1 (t) is connected to the most energetic fluctuations in the flow: the large scale jet oscillation. 34 Figure 4 shows a distribution of the fraction of kinetic energy present in the temporal modes a n (t) of the POD. It is seen that the fraction of energy contained in the first mode a 1 (t) is 39%.…”

Section: Jet Oscillations Without Lorentz Forcing (N = 0)mentioning

confidence: 99%

Effects of electromagnetic forcing on self-sustained jet oscillations

et al. 2014

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The influence of electromagnetic forcing on self-sustained oscillations of a jet issuing from a submerged nozzle into a thin vertical cavity (width W much larger than thickness T) has been studied using particle image velocimetry. A permanent Lorentz force is produced by applying an electrical current across the width of the cavity in conjunction with a magnetic field from three permanent magnets across its thickness. As a working fluid a saline solution is used. The magnetic field is in the north-south-north configuration, such that the Lorentz force can be applied in an up-down-up configuration or in a down-up-down configuration by switching the direction of the electrical current. A critical Stuart number Nc was found. For N < Nc, the jet oscillates with a constant Strouhal number St, independent of the Reynolds number Re. For N > Nc and an oscillation enhancing up-down-up configuration of the Lorentz force, St grows with N as St \documentclass[12pt]{minimal}\begin{document}$\propto \sqrt{\mathrm{N}}$\end{document}∝N. In contrast, for N > Nc and an oscillation suppressing down-up-down configuration of the Lorentz force, all jet oscillations are suppressed.

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“…DMD has been developed and applied extensively in the fluid dynamics community where numerically solving a set of complex governing equations for the purpose of bifurcation analysis or development of controllers is computationally prohibitive [49,51,54,55,57]. Other fluid dynamics applications include shockwave-turbulent boundary layer interactions [53], cavity flows [105,108], detonation waves [109] and jets [110]. The method has also been applied to problems where the underlying governing equations are not well-described, such as epidemiology [58], neuroscience [59], and computer vision problems such as foreground/background separation in video streams [60].…”

Section: The Dynamic Mode Decompositionmentioning

confidence: 99%

Including inputs and control within equation-free architectures for complex systems

Proctor

Brunton

Kutz

2016

Eur. Phys. J. Spec. Top.

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Abstract. The increasing ubiquity of complex systems that require control is a challenge for existing methodologies in characterization and controller design when the system is high-dimensional, nonlinear, and without physics-based governing equations. We review standard model reduction techniques such as Proper Orthogonal Decomposition (POD) with Galerkin projection and Balanced POD (BPOD). Further, we discuss the link between these equation-based methods and recently developed equation-free methods such as the Dynamic Mode Decomposition and Koopman operator theory. These data-driven methods can mitigate the challenge of not having a well-characterized set of governing equations. We illustrate that this equation-free approach that is being applied to measurement data from complex systems can be extended to include inputs and control. Three specific research examples are presented that extend current equation-free architectures toward the characterization and control of complex systems. These examples motivate a potentially revolutionary shift in the characterization of complex systems and subsequent design of objective-based controllers for data-driven models.

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Analysis of time-resolved PIV measurements of a confined turbulent jet using POD and Koopman modes

Cited by 124 publications

References 23 publications

Upstream shear-layer stabilisation via self-oscillating trailing edge flaplets

Upstream shear-layer stabilisation via self-oscillating trailing edge flaplets

Effects of electromagnetic forcing on self-sustained jet oscillations

Including inputs and control within equation-free architectures for complex systems

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