E. Caraballo

Large-scale structure evolution and sound emission in high-speed jets : real-time visualization with simultaneous acoustic measurements

This investigation presents a unique and elaborate set of experiments relating the generation of noise to the evolution of large-scale turbulence structures within an ideally expanded, Mach 1.28, high-Reynolds-number

Feedback control of subsonic cavity flows using reduced-order models

(1.03\,{\times}\,10^{6})

Exploring strategies for closed-loop cavity flow control

jet. The results appear to indicate many similarities between the noise generation processes of high-speed low-Reynolds-number and high-speed high-Reynolds-number jets. Similar to the rapid changes observed in theregion of noise generation in low-Reynolds-number jets in previous experimental and computational work, a series of robust flow features formed approximately one convective time scale before noise emission and then rapidly disintegrated shortly before the estimated moment of noise emission. Coincident with the disintegration, a positive image intensity fluctuation formed at the jet centreline in a region that is immediately past the endof the potential core. This indicates mixed fluid had reached the jet core. These results are consistent with the formation of large-scale structures within the shear layer, which entrain ambient air into the jet, and their eventual interaction and disintegration apparently result in noise generation. These results are quite different from the evolution of the jet during prolonged periods that lacked significant sound emission. The observations presented in this work were made through the use of well-established technique that were brought together in an unconventional fashion. The sources of large-amplitude sound waves were estimated in time and three-dimensional space using a novel microphone array/beamforming algorithm while the noise-generation region of the mixing layer was simultaneously visualized on two orthogonal planes (one of which was temporally resolved). The flow images were conditionally sampled based on whether or not a sound wave wascreated within the region of the flow while it was being imaged and a series of images was compiled that was roughly phase-locked onto the moment of sound emission. Another set of images was gathered based on a lack of sound waves reaching the microphone array over several convective time scales. Proper orthogonal decomposition (POD) was then used tocreate a basis for the flow images and this basis was used to reconstruct the evolution of the jet.

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

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 10 5 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 uses 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 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.

Effects of open-loop and closed-loop control on subsonic cavity flows

One of the current three main thrust areas of the Collaborative Center of Control Science (CCCS) at The Ohio State University is feedback control of aerodynamic flows. Synergistic capabilities of the flow control team include all of the required multidisciplinary areas of flow simulations, low-dimensional and reduced-order modeling, controller design, and experimental integration and implementation of the components along with actuators and sensors. The initial application chosen for study is closed-loop control of shallow subsonic cavity flows. We have made significant progress in the development of various components necessary for reduced-order model based control strategy, which will be presented and discussed in this paper. Stochastic estimation was used to show that surface pressure measurements along with the reduced-order model based on flow-field variables can be used for closed-loop control. Linear controllers such as H ∞ , Smith predictor, and PID were implemented experimentally with various degrees of success. The results showed limitations of linear controllers for cavity flow with inherent nonlinear dynamics. Detailed experimental work further explored the physics and showed the highly non-linear nature of the cavity flow and the effects of forcing on the flow structure.

Application of Proper Orthogonal Decomposition to a Supersonic Axisymmetric Jet

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.

Feedback Control of Cavity Flow Using Experimental Based Reduced Order Model

This work presents an experimental investigation of the effects of open- and closed-loop control techniques on the flow structure and surface pressure signature in subsonic cavity flows. The cases include the uncontrolled (baseline) Mach 0.30 flow over a shallow cavity of aspect ratio 4 with Reynolds number based on the cavity depth of 105, and four actively controlled flows. The controlled cases include open-loop at two discrete frequencies and two closed-loop cases: parallel proportional with time delay and reduced-order model-based linear quadratic. Measurements and analyses include particle image velocimetry, spectra and spectrograms of surface pressure and velocity fluctuations, flow visualization, and proper orthogonal decomposition. Data are presented and analyzed in an effort to better understand the behavior of the cavity flow in response to a variety of actuation cases. Results show that both open- and closed-loop control have significant effects on the flow dynamics and surface pressure behavio...

Closed-Loop Active Flow Control - A Collaborative Approach

Results are presented from the application of the snapshot proper orthogonal decomposition (POD) method to a spatiotemporal e owe eld generated from large eddy simulations (LES) of a Mach 1.4 ideally expanded jet. This is part of ongoing research in the development and use of the POD method in conjunction with advanced laser-based optical measurementsin high-speed e ows.ThePOD application goal istwofold: to extract dynamically signie cant information on the large-scale coherent structures in a high-speed jet and to facilitate low-dimensional modeling of the jet. It was found that the spatial eigenmodes obtained using weakly correlated snapshots, but spanning tens of convective timescale and uncorrelated snapshots, are similar. It was also found that a shortduration temporally resolved LES data (simulating data obtainable from pulse burst laser-based measurements ) could be used to calculate the time evolution coefe cients of the eigenmodes. The use of a few modes (namely, 12) was sufe cient for a reasonable reconstruction of the spatiotemporal e owe eld. The use of POD with a vector norm instead of a scalar norm did reduce the energy captured in the e rst few modes and also changed their rank order, but did not substantially alter the reconstructed e ow. In the early jet development region, the e rst and dominant mode was found to be axisymmetric, followed by either another axisymmetric or asymmetric (probably helical ) mode, whereas higher modes in this region and all ofthemodes fartherdownstream weremorecomplex and threedimensional. The POD modes and their temporal coefe cients obtained at various streamwise locations suggest that the large-scale jet structures undergo a process of disorganization near the end of potential core, followed by reorganization farther downstream.

Control Input Separation Methods for Reduced-Order Model-Based Feedback Flow Control

We present preliminary results on subsonic cavity flow control using reduced-order model based feedback control derived from experimental measurements. The reduced-order model was developed using the Proper Orthogonal Decomposition of PIV results in conjunction with the Galerkin projection of the Navier-Stokes equations onto the resulting spatial eigenfunctions. The stochastic estimation method was used for real-time estimate of the model time coefficients from dynamic surface pressure measurements. Equilibrium analysis led to the linearization of the reduced-order model around the equilibrium point and a model for controller design was obtained by shifting the origin of the coordinates to the equilibrium point. A linear-quadratic optimal controller was then designed and tested in the experiments. The results obtained are very promising and show that control is capable of reducing the cavity flow resonance not only at the Mach 0.3 flow, for which the reducedorder model was specifically derived, but also at other flows with some variation of the Mach number. These preliminary results indicate that the control switches the flow from a single mode resonance to a multi-mode resonance.

Further Development of Feedback Control of Cavity Flow Using Experimental Based Reduced Order Model

The Collaborative Center of Control Science (CCCS) at The Ohio State University was founded very recently with funding from the Air Force Research Laboratory to conduct multidisciplinary research in the area of feedback control, with applications such as cooperative control of unmanned air vehicles (UAVs), guidance and control of hypersonic vehicles, and closed-loop active flow control. The last topic is the subject of this paper. The goal of this effort is to develop tools and methodologies for the use of closedloop aerodynamic flow control to manipulate the flow over maneuvering air vehicles and ultimately to control the maneuvers of the vehicles themselves. It is well known in the scientific community that this is a challenging task and requires expertise in flow simulation, low dimensional modeling of the flow, controller design, and experimental integration and implementation of these components along with actuators and sensors. The CCCS flow control team possesses synergistic capabilities in all these areas, and all parties have been intimately involved in the project from the beginning, a radical departure from the traditional approach whereby an experiment is designed and constructed, data are collected, a model is developed, and a control law is designed, i.e. the system is assembled for validation in a sequential fashion. The first problem chosen for study, control of the noise created by a shallow cavity placed in a flow, has specific relevance to the needs of the Air Force. For example, significant pressure fluctuations in an aircraft weapon bay can lead to structural damage to the air vehicle, to the stores carried in the cavity, and especially to the electronics carried onboard the stores. The team has been working together for a relatively short period of time. Nevertheless, significant progress has been made in the development of various components of the closed-loop cavity flow control problem. The paper will present and discuss the progress made to date and future plans.