The prediction of airflow-generated noise in ducts from considerations of similarity

Oldham, DJ; Waddington, DC

Abstract

In recent years, there have been a number of attempts to devise generalized prediction techniques for airflow-generated noise [1]. A technique based upon the static pressure loss due to in-duct elements which built upon the earlier work of Nelson and Morfey [2] has recently been proposed by the authors [3]. In this paper, we describe how the Nelson and Morfey work can also be employed as the starting point of an alternative technique based upon aerodynamic and acoustical similarity.

Many fluid-flow situations are of such complexity that they cannot be modelled using analytical techniques. An alternative approach is to use data measured on one con"guration to predict the behaviour of another con"guration which is su$ciently similar for simple scaling laws to be applied. For example, this is the basis of the wind-tunnel testing of scale models to determine the drag characteristics of dynamic objects. In employing similarity in this way, it is necessary to identify relevant dimensionless groupings of parameters. The Strouhal number is such a dimensionless grouping and its most well-known application is to relate the frequency of vortex shedding from a cylindrical spoiler in an air stream to the velocity of the airflow and the diameter of the spoiler. The Strouhal number is also frequently employed to normalize spectral data relating to the noise generated by in-duct flow spoilers (see, for example, reference [4]).

In this paper, we show how similarity can be used to predict the airflow noise generated by common types of duct components.

Citation

Oldham, D., & Waddington, D. (2001). The prediction of airflow-generated noise in ducts from considerations of similarity. Journal of Sound and Vibration, 248(4), 780-787. https://doi.org/10.1006/jsvi.2001.3721

• Journal Article Type: Article
• Publication Date: Dec 6, 2001
• Deposit Date: Jan 19, 2009
• Journal: Journal of Sound and Vibration
• Print ISSN: 0022-460X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 248
• Issue: 4
• Pages: 780-787
• DOI: https://doi.org/10.1006/jsvi.2001.3721
• Publisher URL: http://dx.doi.org/10.1006/jsvi.2001.3721