A Semi-Empirical Tool for Parameter-Based Helicopter Noise Modeling

A semi-empirical software tool for parameter-based helicopter noise modeling is proposed. The software tool incorporates first-principles models for various helicopter noise sources and calibrates the parameters to match scaled acoustic measurements taken from wind tunnel experiments and/or flight tests for a variety of flight conditions. The tuned models are used to predict the acoustic state of the helicopter inside and outside of the range of the dataset used for calibration. Because the predictions are made using calibrated physics-based models, they generate a more accurate estimate of helicopter noise radiation than traditional interpolation between prerecorded acoustic hemispheres. And since the predictions are made using first-principles models, the predictions can be generated faster and with fewer computational resources than high fidelity rotorcraft models.