Sustainable Marine Structures

Sustainable Marine Operations: Uncertainty-Aware Multi-Body Motion Analysis of Offshore Support Vessels

Suleiman Mohammad

Department of Electronic Marketing and Social Media, Faculty of Economic and Administrative Sciences, Zarqa University, Zarqa 13132, Jordan

Faculty of Business and Communication, INTI International University, Nilai 71800, Malaysia

Yogeesh Nijalingappa

School of Computer Science & Artificial Intelligence, SR University, Warangal 506371, India

Department of Mathematics, Government First Grade College, Tumkur 572101, India

Markala Karthik

Department of Electrical and Electronics Engineering, SR University, Warangal 506371, India

Raja Natarajan

Department of Visual Communication, Sathyabama Institute of Science and Technology, Chennai 600119, India

Hanan Jadallah

Department of Electronic Marketing and Social Media, Faculty of Economic and Administrative Sciences, Zarqa University, Zarqa 13132, Jordan

Azizbek Matmuratov

Department of Pedagogical Sciences, Mamun University, Khiva 220900, Uzbekistan

Asokan Vasudevan

Faculty of Business and Communication, INTI International University, Nilai 71800, Malaysia

School of Management, Shinawatra University, Pathum Thani 12160, Thailand

Business Administration and Management, Wekerle Business School, 1083 Budapest, Hungary

Mashkhura Sultonova

Department of Pedagogy and Psychology, Urgench State University Named after Abu Raykhan Beruniy, Urgench 220100, Uzbekistan

DOI: https://doi.org/10.36956/sms.v7i4.2596

Received: 9 September 2025 | Revised: 17 October 2025 | Accepted: 20 October 2025 | Published Online: 30 December 2025

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Abstract

Offshore support operations must balance safety and sustainability under highly variable sea conditions. Deterministic motion analyses can underestimate extreme vessel responses, leading to insufficient operational limits and increased environmental impact. We develop a fuzzy‐enhanced multi‐body dynamics framework in which key inputs significant wave height, peak period, added mass, and radiation damping are represented as fuzzy numbers. An α-cut decomposition yields interval bounds at each confidence level, and a fourth-order Runge-Kutta scheme integrates the six-degree-of-freedom equations of motion for both lower and upper “vertex” systems. A case study off the Karnataka coast applies both full 6-DoF and single-DOF heave approximations to demonstrate methodology. The heave response envelopes under calm (nominal α = 1: 0.73 m; full range at α = 0: 0.64–1.64 m) and severe (nominal 1.58 m; range 1.32–2.36 m) sea states reveal potential underestimations of 124 % and 49 %, respectively, when using only nominal values. By selecting an operational α-level (e.g., α* = 0.35 to cap heave ≤ 1.8 m), decision-makers can balance risk tolerance and conservatism. Sensitivity analysis identifies significant wave height as the dominant uncertainty driver. Computational trade-offs and adaptive α-sampling strategies are discussed. This work provides a self-contained, uncertainty-aware tool for deriving operational envelopes that improve risk-informed planning and enable fuel-efficiency optimization. By embedding fuzzy uncertainty quantification into vessel dynamics, the methodology supports safer, more sustainable marine operations and can be extended to real-time sensor fusion, multi-vessel interactions, and frequency-dependent hydrodynamics.

Keywords: Fuzzy Uncertainty Quantification; α-Cut Interval Analysis; Hydrodynamic Modeling; Sea-State Spectrum Modeling; Heave Response Envelope; Operational Risk Assessment; Fuel Consumption Optimization

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