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Statistical Analysis and Prediction for Behaviors of Tracked Vehicle Traveling on Soft Soil Using Response Surface Methodology  

Lee Tae-Hee (Hanyang Univeristy, School of Mechanical Engineering)
Jung Jae-Jun (Hanyang Univeristy, School of Mechanical Engineering)
Hong Sup (Ocean Development System Laboratory, KORDI)
Km Hyung-Woo (Ocean Development System Laboratory, KORDI)
Choi Jong-Su (Ocean Development System Laboratory, KORDI)
Publication Information
Journal of Ocean Engineering and Technology / v.20, no.3, 2006 , pp. 54-60 More about this Journal
Abstract
For optimal design of a deep-sea ocean mining collector system, based on self-propelled mining vehicle, it is imperative to develop and validate the dynamic model of a tracked vehicle traveling on soft deep seabed. The purpose of this paper is to evaluate the fidelity of the dynamic simulation model by means of response surface methodology. Various statistical techniques related to response surface methodology, such as outlier analysis, detection of interaction effect, analysis of variance, inference of the significance of design variables, and global sensitivity analysis, are examined. To obtain a plausible response surface model, maximum entropy sampling is adopted. From statistical analysis and prediction for dynamic responses of the tracked vehicle, conclusions will be drawn about the accuracy of the dynamic model and the performance of the response surface model.
Keywords
Deep-sea ocean mining system; Self-propelled mining system; Rigid body model of tracked vehicle; Response surface methodology;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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