Strategies of Flow Control via Resolvent Analysis with Applications in Airframe Noise

Abstract

The current proposal describes the plan associated to the research internship (BEPE) of student Tulio Rodarte Ricciardi. The internship will be held in the Department of Mechanical and Aerospace Engineering at University of California Los Angeles (UCLA). During this period, Tulio will work under the supervision of Prof. Kunihiko Taira who has extensive expertise in the fields of flow modal decomposition, high-performance computing and flow control, which are topics related to the present research proposal.In recent years, advances in computational power allowed large-scale numerical simulations of turbulent flows including their noise generation and propagation. In order to perform a thorough analysis of the computed flows, advanced post-processing techniques are required. Techniques based on flow modal decomposition, linear stability analysis and resolvent analysis can provide further insights into the flow physics, being useful for flow control and noise prediction. For instance, understanding the process of flow transition and the role of fluid-structure interaction is fundamental for developing noise mitigation strategies via passive and active flow control in unsteady flows. Besides noise reduction, flow control can also be useful for drag reduction, lift increase, and mixing and heat transfer enhancement.In this project, we aim to combine high-fidelity flow simulations, aeroacoustic predictions and resolvent analysis to develop flow control strategies for unsteady flows. The applications in mind will consider configurations relevant for airframe aeroacoustics. One of the main noise sources of commercial aircraft are due to landing gears, where turbulent coherent structures can excite cavity resonance modes that generate intense far-field tonal noise. We will perform numerical simulations and acoustic predictions of configurations representative of landing gear cavities. Resolvent analysis will be employed to provide information in terms of response to perturbations over a range of frequencies. Hence, we will gain insights into identifying the effective unsteady forcing that requires minimal energy to modify the mean flow. Such knowledge is crucial for mitigation of noise sources within the flow field at minimum cost. The model flows investigated here at subsonic speeds and moderate to high Reynolds numbers will present a rich flow dynamics consisting of fluid-structure interaction from turbulence impinging on sharp edges of the cavity, besides acoustic resonances and scattering. The ultimate goal of this work is to develop strategies for reducing far-field noise by means of optimal flow control.