Strength design of a knuckle component using moving least-squares response-surface-based approximate optimization methods

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

Volumn 223, Issue 8, 2009, Pages 1019-1032

  Song, C Y ^a   Lee, J S ^a  

^a Yonsei University   (South Korea)

Author keywords

Approximate optimization; Automotive knuckle; Constraint feasible moving least squares method; Moving least squares method; Strength design

Indexed keywords

ABAQUS; BRAKES; CONSTRAINT THEORY; DEFORMATION; DESIGN; STRENGTH OF MATERIALS; SURFACE PROPERTIES;

APPROXIMATE OPTIMIZATION; AUTOMOTIVE KNUCKLE; INEQUALITY CONSTRAINT; MOVING LEAST SQUARES; MOVING LEAST SQUARES METHOD; MOVING LEAST SQUARES METHODS (MLSM); STRENGTH DESIGN; VEHICLE SPECIFICATION;

LEAST SQUARES APPROXIMATIONS;

EID: 68849093299     PISSN: 09544070     EISSN: None     Source Type: Journal    
DOI: 10.1243/09544070JAUTO1163     Document Type: Article

References (19)

1. Crouse, H. W. and Anglin, L. D. Automotive mechanics, 1993 (McGraw-Hill, New York).
2. Choi, C. and Bae, K. I. The stress analysis of chassis component in the early stage of vehicle development. Trans. KSME A, 1996, 3(9), 876-885.
3. Taylor, D., Esmen, E. A., Crowley, J., and Pan, J. Determination of assembly stresses in aluminum knuckles. SAE Trans., 1999, 108(5), 302-306.
4. Leclère, G., Nême, A., Cognard, J. Y., and Berger, F. Rupture simulation of 3D elastoplastic structures under dynamic loading. Comput. Structs, 2004, 82, 2049-2059.
5. Zoroufi, M. and Fatemi, A. Fatigue life comparisons of competing manufacturing processes: a study of steering knuckle. SAE paper 2004-01-0628, 2004.
6. Fourlaris, G., Ellwood, R., and Jones, T. B. The reliability of test results from simple test samples in predicting the fatigue performance of automotive components. Mater. Des., 2007, 28, 1198-1210.
7. Krishna, M. M. R. Finite element shape optimization of a steering knuckle for a heavy truck - a case study. SAE paper 2001-01-0634, 2001.
8. Lee, J., Jeong, H., and Kang, S. Derivative and GA based methods in meta-modeling of back-propagation neural networks for constraint approximate optimization. Struct. Multidisciplinary Optimization, 2008, 35(1), 29-40.
9. Lee, J., Jeong, H., Choi, D. H., Volovoi, V., and Mavris, D. An enhancement of constraint feasibility in BPN based approximate optimization. Comput. Methods Appl. Mech. Engng, 2007, 196, 2147-2160.
10. Lee, J. and Kang, S. GA based meta-modeling of BPN architecture for constrained approximate optimization. Int. J. Solids Structs, 2007, 44, 5980-5993.
11. Picheny, V., Kim, N. H., and Haftka, R. T. Conservative predictions using surrogate modeling. In Proceedings of the 49th AIAA/ASME/ASCE/ AHS/ASC Structures, Structural Dynamics, and Materials Conference, Schaumburg, Illinois, USA, 7-10 April 2008, paper AIAA-2008-1716 (American Institute of Aeronautics and Astronautics, Reston, Virginia).
12. Haftka, R. T. Using bootstrap methods for conservative estimations of probability of failure. In Proceedings of the 2006 NSF Design, Service, and Manufacturing Grantees and Research Conference, St Louis, Missouri, USA, 24-27 July 2006 (National Science Foundation, Arlington, Virginia).
13. Kim, C. and Choi, K. K. Reliability-based design optimization using response surface method with prediction interval estimation. J. Mech. Des., 2008, 130, 121401-1-121401-12. 14 ABAQUS user's manual version 6.8, 2008 (Dassault Syste'mes Simulia, Providence, Rhode Island).
14. Matschinsky, W. Road vehicle suspensions, 1998 (John Wiley, New York).
15. Lancaster, P. and Salkauskas, K. Curve and surface fitting: an introduction, 1986 (Academic Press, New York).
16. Zou, T., Mourelatos, Z. P., Mahadevan, S., and Tu, J. An indicator response surface method for simulation-based reliability analysis. J. Mech. Des., 2008, 130, 071401-1-071401-11.
17. Belegundu, A. D. and Chandrupatla, T. R. Optimization concept and applications in engineering, 1999 (Prentice-Hall, Upper Saddle River, New Jersey).
18. Wolfe, P. A duality theorem for nonlinear programming. Q. Appl. Math., 1961, 19, 239-244.
19. Mangasarian, O. L. Nonlinear programming, 1969 (McGraw-Hill, New York).