PIANO: A physics-based semi-empirical source level model for fleet-scale ship URN prediction

Concern is growing about the impacts of continuous underwater radiated noise (URN) from ships on marine fauna. In anticipation of future regulation new tools are needed for the assessment of ship URN, covering predictions for individual vessels up to basin-scale soundscapes. In this paper we describe the development of a physicsbased semi-empirical source level model for predicting propeller cavitation noise and machinery noise of ships, which we call the PIANO model. The new model is designed to be applied efficiently at fleet scale, together with Automatic Identification System and ship particulars data, for the generation of sound maps. Furthermore, the model is suitable for use in forecast scenarios in which the effects of mitigation measures on URN are studied. A description of the model is presented, together with an overview of the required input parameters. Improvements on the state-of-the-art are summarised. Results of model validation using measurements from the Enhancing Cetacean Habitat and Observation (ECHO) Program are reported. Overall the new model provides a higher degree of predictive capability compared to existing models while exhibiting similar levels of accuracy and uncertainty. Despite having been developed for sound mapping studies, it can also be used for early design stage URN predictions.