Component-wise regression sound source models for the aircraft noise prediction framework J-FRAIN

Abstract

In this study, we created sound source models for a newly developed simulation framework named 'J-FRAIN' that can accurately predict the time histories of noises from each major aircraft noise-generating component at ground observation points during the landing approach phase. Sound source distributions of more than twenty types of jet transport aircraft have been measured in flight using a microphone array deployed under the final approach path to an airport. In this paper, the Boeing 787-8 is presented as an example for modeling. The sound powers of each aircraft component - engines, landing gear, and high-lift devices - were calculated quantitatively from the domain integration of the measured acoustic maps. Then, component-wise regression sound source models were created based on the relationship between engine rotational speed, airspeed, and deployment angle of high-lift devices. The models were implemented in the 'J-FRAIN' simulation framework that integrates a sound propagation model. The predicted time histories of ground noise were compared with measurement results from a single microphone placed at the center of the microphone array, and were found to be in good agreement.