Towards a universal scaling for broadband turbulent noise in internal flow devices
conference paper
An investigation is performed on the scalability of broadband noise sources from separated flows in internal pipe systems. Broadband sources from for example wellhead chokes, bends and valves can potentially excite subsea manifolds through fluid acoustic coupling and fluid structural coupling. The focus of the current work is evaluation and improvement of scaling laws for collapse of sound power spectra. The approach proposed here is to use steady-state Computational Fluid Dynamics [CFD] to better estimate the properties of the flow in order to improve the scaling law and obtain a universal broadband spectrum. Steady Reynolds Averaged Navier-Stokes [RANS] simulations of several bend and orifice geometries have been performed. A surface acoustic power model based on modeled turbulent quantities is implemented. Based on the RANS data, more advanced models for scaling have been developed. Experimental sound power spectra from literature of the simulated geometries are scaled using different methodologies in both amplitude and frequency. When a new scaling based on CFD modeled surface acoustic power was used, a universal collapse among geometries occurred. Using CFD, the velocity in the high-speed sound-producing region is obtained, as well as a more accurate length scaling in order to improve the frequency scaling. A vast improvement in collapse over different geometries is achieved. The current work indicates that a universal collapse might indeed be present. The methodology does not require high fidelity calculations and is thus easy to implement. By comparing original and new scaling laws, it turns out that the ratio of fluctuating drag over steady drag can vary among geometries.
Topics
TNO Identifier
513298
ISBN
9780791856437
Publisher
American Society of Mechanical Engineers
Source title
ASME 2013 International Mechanical Engineering Congress and Exposition, IMECE 2013, 15-21 November 2013, San Diego, CA, USA
Files
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