Semi-empirical Rotorcraft Acoustics Model using Parameter Identification Techniques

US warfighter safety could be significantly improved by providing an ability to quickly and accurately assess the acoustic impact of rotorcraft operations in the field and reduce the likelihood of detection. Current mission planning tools are empirical in nature, limited to operating conditions for which flight test data exists and challenged in predicting the acoustic impact of maneuvering flight. First-principles models capable of predicting acoustics beyond the range of test data cannot produce helicopter noise spheres with the accuracy of empirical models nor in the time frame required by mission planners. The solution proposed here is to develop a time-domain based hybrid method, in which a mid-fidelity, physics-based helicopter aeroacoustic model is calibrated to measured data using parameter identification techniques to provide accuracy comparable to current empirical models where measured data exists and superior to current empirical models for flight conditions where measured data does not exist. This includes accurate extrapolation from steady flight data to maneuvering flight predictions. Existing, validated, mid-fidelity, commercially-available helicopter aeroacoustic prediction software will be calibrated to measured data using parameter identification methods tailored specifically for use in this application based on insights drawn from the experience of the proposing team and Phase I research.