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

Cited 1 time in WEB OF SCIENCE Cited 2 time in Scopus
Title
Study on the Design of an Underwater Chain Trencher via a Genetic Algorithm
Author(s)
Kim, Jaebum; Kwon, O. Soon; Nguyen Le Dang Hai; Ko, Jin Hwan
KIOST Author(s)
Kwon, O Soon(권오순)
Alternative Author(s)
권오순
Publication Year
2019-12
Abstract
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.
ISSN
2077-1312
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/40274
DOI
10.3390/jmse7120429
Bibliographic Citation
JOURNAL OF MARINE SCIENCE AND ENGINEERING, v.7, no.12, 2019
Publisher
MDPI
Keywords
chain trenching machine; analytical model; multi-objective optimization; genetic algorithm
Type
Article
Language
English
Document Type
Article
Publisher
MDPI
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