University of Mississippi
Statistical Scaling of Turbulent Surface Pressure in the Atmospheric Boundary Layer
Abstract
dc:description.abstract<p>Turbulence in the atmosphere produces fluctuations in static pressure through a variety of mechanisms. These fluctuations are of interest both to atmospheric scientists, as a fluid dynamic property, and to acousticians, as a source of wind noise. At the ground surface, previous work has found the dominant source of pressure fluctuations to be an interaction of the turbulent vertical velocity with the shear rate in the mean wind. In this work, the existing theoretical framework was extended to investigate the effects of atmospheric stability, shear anisotropy, and different turbulence models. A rapid-distortion model was introduced and compared with the existing mirror-flow model. Solutions for the surface pressure spectra from each model were derived, and a method for estimating the model parameters from average elevation-dependent flow properties was developed. In order to validate and compare these spectral models, an experiment was conducted in Laramie, Wyoming to obtain measurements of low-frequency surface pressure simultaneous with the boundary-layer meteorology over a wide range of atmospheric conditions. The velocity data were then used to fit the turbulence model parameters, and predictions of the surface pressure spectra were made. These predictions were compared with the spectra of the surface pressure measurements over half-hour intervals, converted to wavenumber space by introducing a convection velocity. In stable conditions, a low-wavenumber amplification of the spectrum was observed, in accordance with predictions. In convection conditions, the rapid-distortion model performed best, and the shear anisotropy contained in this model was found to be relevant to fitting nearly-neutral cases. The modification of the spectral structure by the shear-anisotropic model suggests a possible unifying mechanism for discrepancies between engineering and atmospheric boundary-layer pressure statistics.</p>
Degree
thesis:*- Name thesis:degree_name
- Ph.D. in Engineering Science
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Electrical Engineering
- Year dc:date.available
- 2016
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Lyons, Gregory William
- Contributors dc:contributor
-
- Nathan E. Murray
- Carrick L. Talmadge
- Richard Raspet
Subjects
dc:subject × 7Identifiers
dc:identifier.*- Repository record dc:identifier
- https://egrove.olemiss.edu/etd/1390
- OAI identifier oai:identifier
- oai:egrove.olemiss.edu:etd-2389