Research on a novel hull, main engine and propeller matching design framework

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Authors: Yang Zhao, Meng-Hong Yu, Wei Yuan, Zhen Su, Chu-Wen Shen
Cited by: 0
References: 22

Abstract

Amid the transition toward a low-carbon and green economy, major shipyards worldwide are fully booked with production schedules extending beyond 2030. The propulsion system is central to a ship, and the coordinated matching of the hull, main engine, and propeller is crucial for improving navigational efficiency. Current design methods are time-consuming, labor-intensive, and inadequate to meet industry demands. To accelerate the ship design efficiency and lower the technical threshold, this paper proposes a novel matching design framework for hull-main engine-propeller integration, which comprises four phases: initialization, match, pick, and rank. In initialization phase, partial parameters of candidate solutions are assigned. In match phase, it introduces a self-adjusting method for the A e / A o , using cavitation verification results to refine the design scheme and complete remaining parameters. In pick phase, it applies constraints based on objective principles and expert experience to identify high-quality feasible solutions as "winners." In rank phase, winners are ranked via Pareto dominance according to the open-water efficiency at design speed and maximum speed to determine the optimal solution. Six design experiments on four vessels yielded 53, 19, 26, and 115 winners, accounting for 4.30%, 1.54%, 1.06%, and 4.67% of the population, respectively. The average open-water efficiencies of the optimal solutions reached 72.13%, 74.52%, 70.19%, and 59.07%. Compared to existing methods, the proposed framework shows lower parameter sensitivity, requires no manual intervention, and delivers design sets with greater diversity and superiority. This helps to shorten the ship design cycle and promote the development of the shipping industry.

Fields of Study & Subjects

Ship Hydrodynamics and Maneuverability Maritime Transport Emissions and Efficiency Advanced Multi-Objective Optimization Algorithms

Publication details

Journal / source
Results in Engineering
Volume
29
Pages
109296–109296
Publication date
28 January 2026
Language
EN