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http://dx.doi.org/10.26748/KSOE.2021.002

Surrogate Model Based Approximate Optimization of Passive Type Deck Support Frame for Offshore Plant Float-over Installation  

Lee, Dong Jun (Department of Naval Architecture & Ocean Engineering, Mokpo National University)
Song, Chang Yong (Department of Naval Architecture & Ocean Engineering, Mokpo National University)
Lee, Kangsu (Korea Research Institute of Ships & Ocean Engineering (KRISO))
Publication Information
Journal of Ocean Engineering and Technology / v.35, no.2, 2021 , pp. 131-140 More about this Journal
Abstract
The paper deals with comparative study of various surrogate models based approximate optimization in the structural design of the passive type deck support frame under design load conditions. The passive type deck support frame was devised to facilitate both transportation and installation of 20,000 ton class topside. Structural analysis was performed using the finite element method to evaluate the strength performance of the passive type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions. The optimum design problem based on surrogate model was formulated such that thickness sizing variables of main structure members were determined by minimizing the weight of the passive type deck support frame subject to the strength performance constraints. The surrogate models used in the approximate optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. In the context of numerical performances, the solution results from approximate optimization were compared to actual non-approximate optimization. The response surface method among the surrogate models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the passive type deck support frame.
Keywords
Passive type deck support frame; Float-over installation; Approximate optimization; Design of experiment; Surrogate model;
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Times Cited By KSCI : 2  (Citation Analysis)
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