• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.98-106
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• 2021

The paper deals with comparative study on sensitivity analysis using various methods regarding to design of experiments for structure design of an active type DSF (Deck support frame) that was developed for float-over installation of offshore plant. The thickness sizing variables of structure member of the active type DSF were considered the design factors. The output responses were defined from the weight and the strength performances. Various methods such as orthogonal array design, Box-Behnken design, and Latin hypercube design were applied to the comparative study. In order to evaluate the approximation performance of the design space exploration according to the design of experiments, response surface method was generated for each design of experiment, and the accuracy characteristics of the approximation were reviewed. The design enhancement results such as numerical costs, weight minimization, etc. via the design of experiment methods were compared to the results of the best design. The orthogonal array design method represented the most improved results for the structure design of the active type DSF.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.187-196
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• 2021

The paper deals with comparative study for characteristics of approximation of design space according to various approximate models and sensitivity analysis using orthogonal array experiments in structure design of active type DSF which was developed for float-over installation of offshore plant. This study aims to propose the orthogonal array experiments based design methodology which is able to efficiently explore an optimum design case and to generate the accurate approximate model. Thickness sizes of main structure member were applied to the design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experiment. Best design case was also identified to improve the structure design with weight minimization. From the orthogonal array experiment results, various approximate models such as response surface model, Kriging model, Chebyshev orthogonal polynomial model, and radial basis function based neural network model were generated. The experiment results from orthogonal array method were validated by the approximate modeling results. It was found that the radial basis function based neural network model among the approximate models was able to approximate the design space of the active type DSF with the highest accuracy.