MUTE-DSS: A Digital-Twin-Based Decision Support System for Minimizing Underwater Radiated Noise in Ship Voyage Planning

TL;DR

This paper introduces MUTE-DSS, a digital-twin-based decision support system that optimizes ship routes and speeds to significantly reduce underwater noise exposure to marine mammals during voyages.

Contribution

It presents a novel integrated framework combining acoustic modeling, real-time computation, and optimization algorithms for noise minimization in ship voyage planning.

Findings

Up to 7.14 dB noise reduction achieved.

Approximately 80.68% reduction in noise exposure in simplified scenarios.

Average 4.90 dB reduction in realistic dynamic settings.

Abstract

We present a novel MUTE-DSS, a digital-twin-based decision support system for minimizing underwater radiated noise (URN) during ship voyage planning. It is a ROS2-centric framework that integrates state-of-the-art acoustic models combining a semi-empirical reference spectrum for near-field modeling with 3D ray tracing for propagation losses for far-field modeling, offering real-time computation of the ship noise signature, alongside a data-driven Southern resident killer whale distribution model. The proposed DSS performs a two-stage optimization pipeline: Batch Informed Trees for collision-free ship routing and a genetic algorithm for adaptive ship speed profiling under voyage constraints that minimizes cumulative URN exposure to marine mammals. The effectiveness of MUTE-DSS is demonstrated through case studies of ships operating between the Strait of Georgia and the Strait of Juan de Fuca, comparing optimized voyages against baseline trajectories derived from automatic identification system data. Results show substantial reductions in noise exposure level, up to 7.14 dB, corresponding to approximately an 80.68% reduction in a simplified scenario, and an average 4.90 dB reduction, corresponding to approximately a 67.6% reduction in a more realistic dynamic setting. These results illustrate the adaptability and practical utility of the proposed decision support system.