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Optimization of the Elastic Joint of Train Bogie Using by Response Surface Model
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 Title & Authors
Optimization of the Elastic Joint of Train Bogie Using by Response Surface Model
Park, Chan-Gyeong; Lee, Gwang-Gi;
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 Abstract
Optimization of the elastic joint of train is performed according to the minimization of ten responses which represent driving safety and ride comfort of train and analyzed by using the each response se surface model from stochastic design of experiments. After the each response surface model is constructed, the main effect and sensitivity analyses are successfully performed by 2nd order approximated regression model as described in this paper. We can get the optimal solutions using by nonlinear programming method such as simplex or interval optimization algorithms. The response surface models and the optimization algorithms are used together to obtain the optimal design of the elastic joint of train. the ten 2nd order polynomial response surface models of the three translational stiffness of the elastic joint (design factors) are constructed by using CCD(Central Composite Design) and the multi-objective optimization is also performed by applying min-max and distance minimization techniques of relative target deviation.
 Keywords
Railway Dynamics;Response Surface Model;Design of Experiments;Optimization;Sensitivity Analysis;Central Composite Design;
 Language
Korean
 Cited by
1.
크리깅 모델에 의한 철도차량 현수장치 최적설계,박찬경;이광기;이태희;배대성;

대한기계학회논문집A, 2003. vol.27. 6, pp.864-870 crossref(new window)
 References
1.
박성현, 1995, 회귀분석, 민영사

2.
박성현, 1995, 현대실험계획법, 민영사

3.
Myers, Montgomery, 1995, Response Surface Methodology - Process and Product Optimization Using Designed Experiments, John Wiley & Sons, New York

4.
Dudley, 1995, 'Multidisciplinary Optimization of the High-Speed Civil Transport,' AIAA Paper 95-1024

5.
Nick Tzannetakis, 1997, 'Numerical Methods for Modeling and Optimization of Noise Emission Applications,' ASME Symposium in Acoustics and Noise Software, Detroit, MI, USA

6.
Bennet, 1998, 'Issues in Industrial Multidisciplinary Optimization,' AIAA Paper 98-4737

7.
BRR, 1998, VAMPIRE User's Manual

8.
LMS, 1998, OPTIMUS User's Guide

9.
Koski, J., 1984, Multi-criteria Optimization in Structural design in New Directions in Optimal Structural design, John Wiley & Sons

10.
Osyczka, 1984, Multi-criteria Optimization in Engineering with FORTRAN Programs, Ellis Horwood Limited

11.
James N. Siddal, 1972, Analytical Decision-Making in Engineering Design, Prentice-Hall