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Currently, there are no FAA-approved software tools suited to accurately model helicopter source noise [1]. An increase in helicopter manufacturing, the rise of the air-taxi, and an increase in vertiport construction, will drive a scarcity of airspace in cities, thus requiring more accurate noise analysis reporting. A tool tailored to the specific source noise of helicopters is needed to create more accurate noise predictions. An affordable, easy to use tool, would also enable helicopter manufacturers to take noise impact into consideration at the design stage, without the need for many costly flight tests. In addition to these two civilian market opportunities the largest government fleet of helicopters belongs to the US ARMY which needs accurate noise predictions for operations. The current, research-level tool for predicting a helicopter’s rotor-harmonic noise is completely reliant on flight test data. This tool is limited and unable to predict noise outside the bounds of a data set and the predictions become inaccurate when modeling between measured conditions [2],[3]. A physics-based semi-empirical approach has been shown to overcome these limitations by first isolating the main rotor harmonic noise sources into separate models, each dependent on a set of predetermined parameters, and then solving an acoustic inverse problem until the difference in predicted and measured noise is minimized [4],[5]. The relationship between the parameters and the acoustic signature is then determined and the noise can be accurately predicted both inside and outside of the scope of any flight test sound measurements. There is an opportunity to implement this methodology in a new software tool so that more accurate noise predictions are possible with less flight test data, improving the state-of-the-art and reducing costs. We propose the Helicopter Acoustics Model (HAM), a mid-fidelity aero-acoustic prediction tool that will implement the demonstrated semi-empirical parameter identification approach.

In developing our HAM proposal, Moshman Research created a Green’s function method for solving the noise field around a helicopter blade section as it revolves. This video shows a noise simulation from a helicopter blade slice revolving five times with a Mach number of 0.85 and an advance ratio of 0.05. The noise field is shown on a grid of receivers in the shape of a southern half-sphere, 3 blade lengths from the center of rotation. The time history of the noise at four receivers in the rotor plane as well as their corresponding frequency spectrum are shown at the end.