Shift2Rail Research Project DESTINATE Interior Railway Noise Prediction Based on OTPA

摘要

Noise abatement generally comes at a cost while offering the benefit of an acoustically preferable solution. In the concept or (re-)design phase for a train, both costs and benefits must be accessible to take informed decisions. Various prediction methods are currently used in the rail industry, that all come with their own advantages and limitations. The Shift2Rail research project DESTINATE aims to support this by developing and advancing acoustic prediction methods. Within this project, an OTPA model was developed to predict interior noise in a light rail vehicle. Various options to utilize the OTPA model in predicting design changes were explored, the most promising one being the integration of FIR filters in the sound synthesis. OTPA results produce rankings for the main noise contributors as well as audible simulations of interior sound signals.