Study on the Design of an Underwater Chain Trencher via a Genetic Algorithm

• Published in: Journal of marine science and engineering Vol. 7; no. 12; p. 429
• Main Authors: Kim, Jaebum, Kwon, O Soon, Hai, Nguyen Le Dang, Ko, Jin Hwan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2019
• Subjects: Algorithms; Chains; Chipping; Compressive strength; Cutting tools; Design; Design optimization; Friction; Genetic algorithms; Kinematics; Multiple objective analysis; Parametric analysis; Traction; Underwater; Weight
• ISSN: 2077-1312; 2077-1312
• DOI: 10.3390/jmse7120429

In this study, a genetic algorithm (GA) with an analytic model is adopted to conduct multi-objective optimization for design of an underwater chain trencher. The optimization problem is defined as minimizing a product of the chain power and weight subject to the uniaxial compressive strength, coefficient of traction, bar length (L), nose radius (R) and ratio of the chipping depth over the spacing (l/S), of which the ranges are determined based on the specifications of commercial trenchers satisfying established performance requirements and previous parametric studies. It is found that an optimal design of the GA was obtained with L and l/S close to their low bound and R far from its low bound while that of a simple parametric analysis was acquired with the three parameters close to their low bounds. Moreover, in the most severe soft rock and traction conditions, the power and weight in the optimal design obtained by the GA are turn to be within the feasible ranges of targeted commercial trenchers.