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NOISE PREDICTION METHODS

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Date Issued:
2020
Abstract/Description:
Noise prediction methods are necessary in aspects of aerodynamic and hydrodynamic engineering. Predictive models of noise from rotating machinery ingesting turbulence is of much interest and relatively recently studied. This thesis presents a numerical method processed in a series of three codes that was written and edited to receive input for geometrical features of rotating machinery, as well as, adjustments to turbulent operating conditions. One objective of this thesis was to create a platform of analysis for any rotor design to obtain five parameters necessary for noise prediction; 1) the hydrodynamic inflow angle to each blade section, 2) chord length as a function of radius, 3) the cylindrical radius of each blade section, 4) & 5) the leading edge as a function of span in both the rotor-plane and as a function of axial distance downstream. Another objective of this thesis was to use computational fluid dynamics (CFD), specifically by using a Reynold’s-Averaged Navier-Stokes (RANS) Shear Stress Transport (SST) 𝑘 − 𝜔 model simulation in ANSYS Fluent, to obtain the turbulent kinetic energy distribution, also necessary in the noise prediction method presented. The purpose of collecting the rotor geometry data and turbulent kinetic energy data was to input the values into the first of the series of codes and run the calculation so that the output spectra could be compared to experimental noise measurements conducted at the Stability Wind Tunnel at Virginia Tech. The comparison shows that the prediction method results in data that can be reliable if careful attention is payed to the input parameters and the length scale used for analysis. The significance of this research is the noise prediction method presented and used simplifies the model of turbulence by using a correlation function that can be determined by a one-dimensional function while also simplifying the iterations completed on rotor blade to calculate the unsteady forces.
Title: NOISE PREDICTION METHODS.
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Name(s): Perry, Nicole Kent , author
Glegg, Stewart , Thesis advisor
Florida Atlantic University, Degree grantor
Department of Ocean and Mechanical Engineering
College of Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2020
Date Issued: 2020
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 206 p.
Language(s): English
Abstract/Description: Noise prediction methods are necessary in aspects of aerodynamic and hydrodynamic engineering. Predictive models of noise from rotating machinery ingesting turbulence is of much interest and relatively recently studied. This thesis presents a numerical method processed in a series of three codes that was written and edited to receive input for geometrical features of rotating machinery, as well as, adjustments to turbulent operating conditions. One objective of this thesis was to create a platform of analysis for any rotor design to obtain five parameters necessary for noise prediction; 1) the hydrodynamic inflow angle to each blade section, 2) chord length as a function of radius, 3) the cylindrical radius of each blade section, 4) & 5) the leading edge as a function of span in both the rotor-plane and as a function of axial distance downstream. Another objective of this thesis was to use computational fluid dynamics (CFD), specifically by using a Reynold’s-Averaged Navier-Stokes (RANS) Shear Stress Transport (SST) 𝑘 − 𝜔 model simulation in ANSYS Fluent, to obtain the turbulent kinetic energy distribution, also necessary in the noise prediction method presented. The purpose of collecting the rotor geometry data and turbulent kinetic energy data was to input the values into the first of the series of codes and run the calculation so that the output spectra could be compared to experimental noise measurements conducted at the Stability Wind Tunnel at Virginia Tech. The comparison shows that the prediction method results in data that can be reliable if careful attention is payed to the input parameters and the length scale used for analysis. The significance of this research is the noise prediction method presented and used simplifies the model of turbulence by using a correlation function that can be determined by a one-dimensional function while also simplifying the iterations completed on rotor blade to calculate the unsteady forces.
Identifier: FA00013487 (IID)
Degree granted: Thesis (M.S.)--Florida Atlantic University, 2020.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Noise
Aerodynamic noise
Hydrodynamics
Noise control--Mathematical models
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00013487
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.