Date of Award
Doctor of Philosophy (PhD)
Mechanical and Aerospace Engineering
Mark N. Glauser
Active Flow Control, Aeroacoustics, Jet Noise, Particle Image Velocimetry, Reduced-Order Modeling, Turbulence
The work to be presented focuses on the noise generation of a fully turbulent, compressible jet flow within a large scale anechoic chamber. The investigations are aimed at understanding the complex nature of the jet flow field in an effort to reduce the far-field noise through active flow control and novel reduced-order modeling. The flow field of a highly subsonic, axisymmetric jet with a nozzle diameter of two inches (50.8 mm), is probed through the implementation of two-component particle image velocimetry (PIV) in the streamwise plane, along the jet's centerline. These measurements are coupled with simultaneously sampled near and far-field pressure measurements, in an effort to understand the relationship between the complex flow field in the near region of the jet and large pressure fluctuation in the far-field, responsible for the noise. In order to reduce these large pressure fluctuations in the acoustic field, it is imperative to first understand the interaction of structures in the flow field and evaluate how this relates to the propagation of acoustic signatures to the far-field.
We seek to establish a low-dimensional representation of the nonlinear, turbulent flow field through the implementation of reduced-order modeling in the form of proper orthogonal decomposition. In the first set of experiments conducted, active flow control is employed in the form of synthetic jet actuation at the nozzle lip, based on previous investigations. The effects of the flow control are observed using large-window PIV and far-field pressure measurements. The results suggest that an order epsilon input elicits an order one response, with both open and closed-loop flow control. While no noise reductions are seen in the far-field as compared to the uncontrolled jet, control authority over the jet is observed. The flow control greatly enhances mixing, thus reducing the length of the potential core and causing shear layer expansion. The second set of experiments involves the implementation of a time-resolved PIV system to effectively capture the temporal evolution of the flow physics in the streamwise plane. Low-dimensional velocity modes are directly correlated to low-dimensional acoustic modes in the far-field, using the observable inferred decomposition. Preliminary findings suggest that a small subset of low-dimensional velocity modes greatly contribute to the far-field acoustics. The spatiotemporal nature of these "loud" modes are investigated in the context of potential noise-producing events. It has been found that for the Mach 0.6 uncontrolled jet, focusing on the region near the collapse of the potential core, modes 6 and 14 appear to be the loud modes, contributing significantly to the far-field noise. Further exploration of mode 6 reveals a unique interaction of structures at very specific instances in time. Thus, it is concluded that from a low-dimensional viewpoint, we have identified the deterministic spatial structures in the velocity that most highly contributes to the noise in the far-field. It is possible from this analysis to begin to identify noise-producing events and examine these interactions in both time and space. Lastly, loud modes are identified for the controlled jet (using time-resolved PIV), however initial findings imply that the control greatly increases the complexity of the problem. Despite this fact, it is found that there may be similarities in the spatial structure of the loud modes for two different closed-loop control cases. In any case, through the use of active flow control and reduced-order modeling, preliminary steps have been taken to understand the sources of jet noise with respect to the flow physics, in an overall effort to efficiently achieve far-field noise reductions for practical applications.
Berger, Zachary P., "The Effects of Active Flow Control on High-Speed Jet Flow Physics and Noise" (2014). Dissertations - ALL. 107.