The influence of two-dimensional hills on simulated atmospheric boundary layers.
Thesis DisciplineMechanical Engineering
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
This thesis describes the development of a number of simulated atmospheric boundary layers and their application to the investigation of wind flow over hills. A review is made of the current knowledge of the wind flow over hills. The atmospheric boundary layer wind tunnel in the Department of Mechanical Engineering was recommissioned and a model 1:300 rural boundary layer established. Measurements of the mean and fluctuating velocities, energy spectra and autocorrelation functions were made in the flow over model two-dimensional triangular hills of slope 3°, 9°, 14° and 27°. Once a certain slope was reached large scale separated flow occurred after the hill crest. The largest increase in velocity occurred for the hill with a slope of 14°. Measurements were also made over round crested hills with the same aspect ratio. Comparison of the flow fields showed that the crest shape had little effect on the flow over the hills. A rural atmospheric boundary layer of 1:3000 scale was established and measurements were made over a selection of the model triangular hills. An increase in the hill height to boundary layer height ratio was found to decrease the amplification factors at the hill crests. Measurements were also made over a number of model triangular hills in an urban model boundary layer of about 1:400 scale which was developed. The effect of the higher velocity gradient was to cause an increase in the amplification factors at the hill crests. A digital data handling system capable of accepting the voltage output from a single hot wire anemometer was developed. Software was written to control the analog to digital converter and transmit the data samples to a minicomputer remote from the wind tunnel. The data samples are stored on disc. When data collection has finished the data is analysed. Software is described which calculates the mean, standard deviation, spectral density function, autocorrelation function and probability density function of the stored data.