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dc.contributor.authorMcBride, Sterling M.en_US
dc.date.accessioned2018-01-23T13:59:07Z
dc.date.available2018-01-23T13:59:07Z
dc.date.issued2017-12-06en_US
dc.identifier.urihttp://hdl.handle.net/10919/81897
dc.description.abstractWind energy is the world´s fastest-growing renewable energy source. Thus, the amount of people exposed to wind farm noise is increasing. Due to its broadband amplitude modulated characteristic, wind turbine noise (WTN) is more annoying than noise produced by other common community/industrial sources. Aerodynamic noise along the blade span is the dominant noise source of modern large wind turbines. This type of noise propagates through the atmosphere in the proximity of wind farms. However, modelling and simulating WTN propagation over large distances is challenging due to the complexity of atmospheric conditions. Real temperature, wind velocity and relative humidity measurements typically show a characteristic nonlinear behavior. A comprehensive propagation model that addresses this problem while maintaining high accuracy and computational efficiency is necessary. A Hamiltonian Ray tracing (HRT) technique coupled to aerodynamically induced WTN is presented in this work. It incorporates acoustic wave refraction due to spatial speed of sound gradients, a full Doppler Effect formulation resulting from wind velocities in any arbitrary direction, proper acoustic energy dissipation during propagation, and ground reflection. The HRT method averts many of the setbacks presented by other common numerical approaches such as fast field program (FFP), parabolic equation methods (PE), and the standard Eikonal ray tracing (ERT) technique. In addition, it is not bounded to the linearity assumptions made for analytic propagation solutions. A wave phase tracking analysis through inhomogeneous and moving media is performed. Curved ray-paths are numerically computed by solving a non-linear system of coupled first order differential equations. Sound pressure levels through the propagation media are then calculated by using standard ray tubes and performing energy analysis along them. The ray model is validated by comparing a monopole’s ray path results against analytically obtained ones. Sound pressure level predictions are also validated against both FFP and ERT methods. Finally, results for a 5MW modern wind turbine over a flat acoustically soft terrain are provided.en_US
dc.format.mediumETDen_US
dc.language.isoenen_US
dc.publisherVirginia Techen_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectAtmospheric Sound Propagationen_US
dc.subjectRay Tracingen_US
dc.subjectWind Turbine Noiseen_US
dc.titleA Comprehensive Hamiltonian Atmospheric Sound Propagation Model for Prediction of Wind Turbine Noiseen_US
dc.typeThesisen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairBurdisso, Ricardo A.en_US
dc.contributor.committeememberTarazaga, Pablo A.en_US
dc.contributor.committeememberRoan, Michael J.en_US
dc.contributor.committeememberSandu, Corinaen_US
dc.description.abstractgeneralModelling propagation of noise produced by wind turbines over large distances is a challenging task. Real temperature distributions, flow characteristics around wind turbines, and relative humidity are some of the parameters that affect the behavior of the produced sound in the atmosphere. To this end, a Hamiltonian ray tracing tool that models the propagation of wind turbine noise has been developed and is the main focus of this thesis. This method avoids many of the limitations and inaccurate assumptions presented by other common numerical and analytical approaches. In addition, current commercial noise propagation codes are incapable of fully capturing the physical complexity of the problem. Finally, validation and simulation results for a wind turbine over flat terrain are presented in order to demonstrate the superior accuracy and computational efficiency of the Hamiltonian approach.en_US


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