Underwater Radiated Noise Management.


The management of Underwater Radiated Noise (URN) on marine platforms is a multifaceted research area with diverse stakeholder interests. URN management involves three main aspects: measurement & analysis, prediction, and alteration to meet specific mission requirements. Various models have been developed for URN prediction, evolving from early research in World War II to modern computational methods like Computational Fluid Dynamics (CFD) and Statistical Energy Analysis (SEA). Measurement and analysis of URN have advanced with the development of standards by organizations like NATO and the Acoustical Society of America (ASA). Regulatory bodies like the International Maritime Organization (IMO) have imposed regulations to mitigate oceanic noise pollution, driving the need for URN management in the maritime industry. 

In the article, URN management is a complex yet crucial aspect of maritime operations, requiring collaboration among stakeholders, advancements in technology, and adherence to regulations to ensure the sustainability of marine ecosystems and the efficiency of maritime activities. The measurement of Underwater Radiated Noise (URN) is subject to various guidelines, regulations, and standards proposed by different classification societies and regulatory bodies, the measurement, regulation, and prediction of URN involve a comprehensive framework of guidelines, regulations, and models developed by classification societies, regulatory bodies, and researchers to address various aspects of underwater noise from ships. 

The paper discusses various models and methods for estimating and analyzing underwater radiated noise (URN) from ships, as well as measurement and analysis techniques. 

Key highlights
  • URN management involves diverse stakeholders with unique interests, including ship designers, naval forces, and marine conservationists. 
  • URN sources are categorized into machinery noise, propulsion machinery noise, and hydrodynamic noise, each presenting distinct challenges. 
  • Advancements in measurement and analysis techniques have been driven by standards developed by organizations like NATO and ASA, along with regulations from IMO. 
  • Regulatory impositions by bodies like IMO aim to mitigate oceanic noise pollution, necessitating URN management in the maritime industry. 
  • Ship design, construction, and operations play vital roles in minimizing URN emissions, emphasizing structural optimization, machinery selection, and maintenance measures. 
  • Standards like ISO and STANAG provide guidelines for URN measurement and analysis, ensuring consistency and accuracy across methodologies. 
  • Provide URN limits for commercial and research vessels, applicable to vessels with specific acoustic design technologies. 
  • Various models like Ross, Randi, Wales-Heitmeyer, and Wittekind, along with computational methods such as SEA, FEM, and CFD, are utilized for predicting underwater radiated noise (URN). 
  • ANSI and ISO standards guide URN measurement, considering factors like water depth, background noise, and transmission loss correction. 
  • Measurement systems include vessel-based, static, and drifting systems, each with specific advantages and limitations. 
Key Challenges
  • Balancing diverse stakeholder interests. 
  • Predicting URN accurately under varying conditions. 
  • Keeping pace with technological advancements. 
  • Coordinating collaborative efforts among stakeholders. 
  • Lack of standardized measurement procedures across classification societies and regulatory bodies. 
  • Difficulty in applying existing standards to various vessel types and environmental conditions, especially in shallow waters. 
  • URN measurement involves complex factors like background noise, transmission loss, and variations in water depth. 
  • Ensuring compliance with diverse regulations from different bodies, which may have varying criteria and thresholds. 
  • Incorporating advancements in ship acoustic design technologies into measurement guidelines and standards. 
  • Access to comprehensive ship parameters for accurate URN prediction is limited, hindering model refinement and validation. 
  • Computational methods like SEA, FEM, and CFD require significant computing resources and time, posing challenges in real-time noise prediction and analysis. 
Major Opportunities 
  • Developing innovative URN prediction and management tools. 
  • Enhancing collaboration between stakeholders for comprehensive URN management. 
  • Investing in green ship technologies to reduce URN emissions. 
  • Opportunity for developing advanced URN measurement technologies and methodologies. 
  • Opportunity to establish unified international standards for URN measurement, promoting consistency and comparability. 
  • Opportunity for classification societies to lead in setting best practices for URN measurement, fostering trust and credibility in the maritime industry. 
  • Leveraging advancements in AI/ML and sensor technologies offers opportunities for real-time noise prediction and monitoring. 
  • Developing standardized measurement procedures facilitates consistent and reliable URN data collection and analysis. 

Maintaining acoustic stealth capabilities for naval operations requires ongoing efforts to predict, analyze, and mitigate URN emissions effectively.

Tupili Yaswanth Reddy, Dr. Arnab Das