Effect of Upstream Mass-Injection on Cavity Flow Oscillations ( PIV Measurements Compared with CFD Predictions)

2003 ◽  
Author(s):  
Ahmad Vakili ◽  
Abraham Meganathan
Keyword(s):  
Cavity Flow ◽  
Piv Measurements ◽  
Mass Injection ◽  
Flow Oscillations ◽  
Cavity Flow Oscillations

Influence of impingement edge geometry on cavity flow oscillations

AIAA Journal ◽  
1994 ◽  
Vol 32 (8) ◽  
pp. 1737-1740 ◽  
Author(s):  
J. C. F. Pereira ◽  
J. M. M. Sousa
Keyword(s):  
Cavity Flow ◽  
Edge Geometry ◽  
Flow Oscillations ◽  
Cavity Flow Oscillations

scholarly journals Effects of Scaling on High Subsonic Cavity Flow Oscillations and Control

2014 ◽  
Vol 51 (2) ◽  
pp. 424-433 ◽  
Author(s):  
V. Thangamani ◽  
K. Knowles ◽  
A. J. Saddington
Keyword(s):  
Cavity Flow ◽  
Flow Oscillations ◽  
Cavity Flow Oscillations ◽  
And Control

Control of Cavity Flow Oscillations by High Frequency Forcing

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
M. A. Martinez ◽  
G. M. Di Cicca ◽  
M. Iovieno ◽  
M. Onorato
Keyword(s):  
Shear Layer ◽  
High Frequency ◽  
Cavity Flow ◽  
Mean Velocity ◽  
Time Resolved ◽  
Piv Measurements ◽  
Sustained Oscillations ◽  
High Frequency Excitation ◽  
Frequency Excitation ◽  
Cavity Flow Oscillations

Time resolved two-dimensional particle image velocimetry (2DPIV) experiments have been conducted to contribute to the understanding of the physics governing the suppression mechanism of cavity flow self-sustained oscillations by means of high frequency excitation of the cavity shear layer. High frequency excitation was introduced by the spanwise coherent vortex shedding in the wake of a cylindrical rod positioned just upstream the cavity entrance, at the edge of the incoming boundary layer. The effectiveness of this suppression was demonstrated for a cavity having the length-to-depth ratio equal to three, in incompressible flow. The spatial and time resolved PIV measurements of the whole flow field in the plane normal to the cavity floor, linear stability analysis of the measured shear layer mean velocity profiles, and preliminary PIV measurements in a plane parallel to the cavity allowed us to offer a better insight into the involved physical mechanisms in suppressing cavity self-sustained oscillations.

scholarly journals Energy harvesting from cavity flow oscillations

2021 ◽  
pp. 1045389X2110149
Author(s):  
Varun Thangamani ◽  
Foo Ngai Kok
Keyword(s):  
Energy Harvesting ◽  
Natural Frequency ◽  
Cavity Flow ◽  
High Amplitude ◽  
Time Frequency ◽  
Feedback Model ◽  
Power Spectral ◽  
Flow Oscillations ◽  
Grazing Flow ◽  
Cavity Flow Oscillations

This study investigates the energy harvesting prospects of self-sustained flow oscillations emanating from grazing flow over a rectangular cavity by employing experimental and computational methods. Two cavity geometries with length-to-depth ratios of 2 and 3, exposed to an incoming flow of 30 m/s, were selected for the purpose. The power spectral density of the baseline cavity flows showed the presence of high-amplitude peaks whose frequencies agreed to those estimated from Rossiter’s feedback model. For energy harvesting, a piezoelectric beam was placed perpendicular to the aft wall and its natural frequency tuned to match closely with the dominant frequencies of the cavity flow oscillations. From the experiments, an average and maximum instantaneous power of 21.11 and 284.18 µW was recorded for the cavity with L/ D = 2 whereas for the cavity with L/ D = 3 the corresponding values were 32.16 and 403.46 µW respectively. Time-frequency analysis showed the forcing of the beam at the cavity oscillation frequency and the substantial increase in the amplitude of beam vibrations when this frequency was close to the natural frequency of the beam.

scholarly journals Reduced-Order Modeling of Cavity Flow Oscillations across Multi-Mach Numbers Using Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Zhe Liu ◽  
Fangli Ning ◽  
Hui Ding ◽  
Qingbo Zhai ◽  
Juan Wei
Keyword(s):  
Deep Learning ◽  
Cavity Flow ◽  
Reduced Order Model ◽  
Flow Conditions ◽  
Order Model ◽  
Reduced Order ◽  
The Future ◽  
Flow Oscillations ◽  
Mach Numbers ◽  
Cavity Flow Oscillations

The reduced-order model can accurately and efficiently predict unsteady problems in many aerospace engineering applications. The traditional reduced-order model based on proper orthogonal decomposition (POD) and Galerkin projection has poor robustness and large error in predicting complex problems. In this paper, a reduced-order model combining POD and deep learning is proposed to predict cavity flow oscillations under different flow conditions. Firstly, POD modes and corresponding coefficients are obtained by POD. Then, two deep learning frameworks, including multilayer perceptron (MLP) and long short-term memory (LSTM) neural networks, are used to predict the future POD coefficients, respectively. Finally, the cavity flow oscillations across multi-Mach numbers are predicted by the POD modes and the future coefficients. The results show that both of these frameworks can accurately predict cavity flow oscillations when the flow conditions change, and the time cost is reduced by order of magnitude. In addition, due to the performance of LSTM is better than that of MLP, its calculation speed is faster.

The effect of a driven bottom wall on cavity flow oscillations

2004 ◽  
Vol 2004 (0) ◽  
pp. 214
Author(s):  
Takashi Yoshida ◽  
Toshihiko IKEDA ◽  
Shouichiro IIO
Keyword(s):  
Cavity Flow ◽  
Bottom Wall ◽  
Flow Oscillations ◽  
Cavity Flow Oscillations

scholarly journals Linear models for control of cavity flow oscillations

2006 ◽  
Vol 547 (-1) ◽  
pp. 317 ◽  
Author(s):  
CLARENCE W. ROWLEY ◽  
DAVID R. WILLIAMS ◽  
TIM COLONIUS ◽  
RICHARD M. MURRAY ◽  
DOUGLAS G. MACMYNOWSKI
Keyword(s):  
Linear Models ◽  
Cavity Flow ◽  
Flow Oscillations ◽  
Cavity Flow Oscillations
Sign in / Sign up

Export Citation Format

Share Document