Tools
Tools
Botha, JDM, Shahrokhi, A and Rice, H (2017) An implementation of an aeroacoustic prediction model for broadband noise from a vertical axis wind turbine using a CFD informed methodology. Journal of Sound and Vibration, 410. pp. 389-415. ISSN 0022-460X
|
Text
JSV_Paper_HR.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview |
Abstract
This paper presents an enhanced method for predicting aerodynamically generated broadband noise produced by a Vertical Axis Wind Turbine (VAWT). The method improves on existing work for VAWT noise prediction and incorporates recently developed airfoil noise prediction models. Inflow-turbulence and airfoil self-noise mechanisms are both considered. Airfoil noise predictions are dependent on aerodynamic input data and time dependent Computational Fluid Dynamics (CFD) calculations are carried out to solve for the aerodynamic solution. Analytical ow methods are also benchmarked against the CFD informed noise prediction results to quantify errors in the former approach. Comparisons to experimental noise measurements for an existing turbine are encouraging. A parameter study is performed and shows the sensitivity of overall noise levels to changes in inflow velocity and inflow turbulence. Noise sources are characterised and the location and mechanism of the primary sources is determined, inflow-turbulence noise is seen to be the dominant source. The use of CFD calculations is seen to improve the accuracy of noise predictions when compared to the analytic ow solution as well as showing that, for inflow-turbulence noise sources, blade generated turbulence dominates the atmospheric inflow turbulence.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 02 Physical Sciences, 09 Engineering |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20) |
| Publisher: | Elsevier BV |
| Date Deposited: | 19 Feb 2019 10:24 |
| Last Modified: | 04 Sep 2021 01:58 |
| DOI or ID number: | 10.1016/j.jsv.2017.08.038 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/10179 |
 |
View Item |