SODAR comparison methods for compatible wind speed estimation

Piper, BJ

Abstract

This thesis includes the results of a PhD study about methods to compare Sonic Detection And Ranging (SODAR) measurements to measurements from other instruments. The study focuses on theoretical analysis, the design of a transponder system for simulating winds and the measurement of the acoustic radiation patterns of SODARs. These methods are integrated to reduce uncertainty in SODAR measurements.
Through theoretical analysis it is shown that the effective measurement volume of a range gate is 15% of a cone section based on the SODAR's Full Width Half Maximum (FWHM). Models of the beam pattern are used to calculate the ratio of air passing a turbine to that measured by a SODAR over 10 minutes with values of 3-5% found at 10ms-1. The model is used to find angles where significant Sound Pressure Levels (SPLs) occur close to a SODARs baffle giving the highest chance of fixed echoes. This is converted into an orientation guide for SODAR set-up.
The design of a transponder system is detailed that aims to provide a calibration test of the processing applied by a SODAR. Testing has shown that the transponder can determine the Doppler shift equation used by a SODAR although further work is needed to make the system applicable to all SODARs.
It is shown that anechoic measurements of single elements are useful for improving array models. Measurements of the FWHM and acoustic tilt angle can be achieved in the field using a tilt mechanism and a Sound Level Meter (SLM) on a 10m mast. The same mechanism can be used to calculate an effective tilt angle using the Bradley technique.
It is proposed that these methods are integrated to calculate error slopes for the SODAR measurement with regards to a secondary location. It is shown that the slopes could be between 0 and 5% if the methods are fully realised and a Computational Fluid Dynamics (CFD) model is incorporated.

Citation

Piper, B. (2011). SODAR comparison methods for compatible wind speed estimation. (Thesis). The University of Salford

• Thesis Type: Thesis
• Deposit Date: Jun 23, 2011
• Publicly Available Date: Apr 5, 2016