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

J. Ocean Eng. Technol. 2006;20(3):54-60.

Lee Tae-Hee;Jung Jae-Jun;Hong Sup;Km Hyung-Woo;Choi Jong-Su;

Hanyang Univeristy, School of Mechanical Engineering;Hanyang Univeristy, School of Mechanical Engineering;Ocean Development System Laboratory, KORDI;Ocean Development System Laboratory, KORDI;Ocean Development System Laboratory, KORDI;

반응표면법에 의한 연약지반 차량 거동의 통계적 분석 및 예측

이태희;정재준;홍섭;김형우;최종수;

한양대학교 기계공학부;한양대학교 기계공학부;한국해양연구원 해양개발시스템연구본부;한국해양연구원 해양개발시스템연구본부;한국해양연구원 해양개발시스템연구본부;

Keywords: Deep-sea ocean mining system, Self-propelled mining system, Rigid body model of tracked vehicle, Response surface methodology

핵심용어: 심해저 채광 시스템, 자항식 채광 시스템, 무한궤도형 주행차량의 강체모델, 반응표면법

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.