A Novel Reduced-Order Model for Predicting Compressible Cavity Flows

2021 ◽  
pp. 1-15
Author(s):  
Zhe Liu ◽  
Fangli Ning ◽  
Qingbo Zhai ◽  
Hui Ding ◽  
Juan Wei
Keyword(s):  
Reduced Order Model ◽  
Cavity Flows ◽  
Order Model ◽  
Reduced Order

scholarly journals Development and Application of a Reduced Order Model for the Control of Self-Sustained Instabilities in Cavity Flows

2013 ◽  
Vol 14 (1) ◽  
pp. 186-218 ◽  
Author(s):  
Kaushik Kumar Nagarajan ◽  
Laurent Cordier ◽  
Christophe Airiau
Keyword(s):  
Time Integration ◽  
Acoustic Mode ◽  
Feedback Mechanism ◽  
Observer Design ◽  
Reduced Order Model ◽  
Cavity Flows ◽  
Order Model ◽  
Reduced Order ◽  
Experimental Implementation ◽  
Proper Orthogonal

AbstractFlow around a cavity is characterized by a self-sustained mechanism in which the shear layer impinges on the downstream edge of the cavity resulting in a feedback mechanism. Direct Numerical Simulations of the flow at low Reynolds number has been carried out to get pressure and velocity fluctuations, for the case of un-actuated and multi frequency actuation. A Reduced Order Model for the isentropic compressible equations based on the method of Proper Orthogonal Decomposition has been constructed. The model has been extended to include the effect of control. The Reduced Order dynamical system shows a divergence in time integration. A method of calibration based on the minimization of a linear functional of error, to the sensitivity of the modes, is proposed. The calibrated low order model is used to design a feedback control of cavity flows based on an observer design. For the experimental implementation of the controller, a state estimate based on the observed pressure measurements is obtained through a linear stochastic estimation. Finally the obtained control is introduced into the Direct Numerical Simulation to obtain a decrease in spectra of the cavity acoustic mode.

Feedback control of subsonic cavity flows using reduced-order models

2007 ◽  
Vol 579 ◽  
pp. 315-346 ◽  
Author(s):  
M. SAMIMY ◽  
M. DEBIASI ◽  
E. CARABALLO ◽  
A. SERRANI ◽  
X. YUAN ◽  
...  
Keyword(s):  
Feedback Control ◽  
Surface Pressure ◽  
Controller Design ◽  
Cavity Flow ◽  
Open Loop ◽  
Reduced Order Model ◽  
Cavity Flows ◽  
Reduced Order Models ◽  
Order Model ◽  
Reduced Order

Development, experimental implementation, and the results of reduced-order model based feedback control of subsonic shallow cavity flows are presented and discussed. Particle image velocimetry (PIV) data and the proper orthogonal decomposition (POD) technique are used to extract the most energetic flow features or POD eigenmodes. The Galerkin projection of the Navier–Stokes equations onto these modes is used to derive a set of nonlinear ordinary differential equations, which govern the time evolution of the eigenmodes, for the controller design. Stochastic estimation is used to correlate surface pressure data with flow-field data and dynamic surface pressure measurements are used to estimate the state of the flow. Five sets of PIV snapshots of a Mach 0.3 cavity flow with a Reynolds number of 105 based on the cavity depth are used to derive five different reduced-order models for the controller design. One model uses only the snapshots from the baseline (unforced) flow while the other four models each use snapshots from the baseline flow combined with snapshots from an open-loop sinusoidal forcing case. Linear-quadratic optimal controllers based on these models are designed to reduce cavity flow resonance and are evaluated experimentally. The results obtained with feedback control show a significant attenuation of the resonant tone and a redistribution of the energy into other modes with smaller energy levels in both the flow and surface pressure spectra. This constitutes a significant improvement in comparison with the results obtained using open-loop forcing. These results affirm that reduced-order model based feedback control represents a formidable alternative to open-loop strategies in cavity flow control problems even in its current state of infancy.

Development and Implementation of an Experimental-Based Reduced-Order Model for Feedback Control of Subsonic Cavity Flows

2007 ◽  
Vol 129 (7) ◽  
pp. 813-824 ◽  
Author(s):  
E. Caraballo ◽  
J. Little ◽  
M. Debiasi ◽  
M. Samimy
Keyword(s):  
Experimental Data ◽  
Feedback Control ◽  
Real Time ◽  
Surface Pressure ◽  
Reduced Order Model ◽  
Estimation Methods ◽  
Cavity Flows ◽  
Pressure Measurements ◽  
Order Model ◽  
Reduced Order

This work is focused on the development of a reduced-order model based on experimental data for the design of feedback control for subsonic cavity flows. The model is derived by applying the proper orthogonal decomposition (POD) in conjunction with the Galerkin projection of the Navier-Stokes equations onto the resulting spatial eigenfunctions. The experimental data consist of sets of 1000 simultaneous particle image velocimetry (PIV) images and surface pressure measurements taken in the Gas Dynamics and Turbulent Laboratory (GDTL) subsonic cavity flow facility at the Ohio State University. Models are derived for various individual flow conditions as well as for their combinations. The POD modes of the combined cases show some of the characteristics of the sets used. Flow reconstructions with 30 modes show good agreement with experimental PIV data. For control design, four modes capture the main features of the flow. The reduced-order model consists of a system of nonlinear ordinary differential equations for the modal amplitudes where the control input appears explicitly. Linear and quadratic stochastic estimation methods are used for real-time estimation of the modal amplitudes from real-time surface pressure measurements.

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