Browse > Article
http://dx.doi.org/10.5574/KSOE.2012.26.6.080

Study of Reliability-Based Robust Design Optimization Using Conservative Approximate Meta-Models  

Sim, Hyoung Min (Dep't of Mechanical Engineering, Graduate School, Yonsei University)
Song, Chang Yong (Dep't of Ocean Engineering, Mokpo National University)
Lee, Jongsoo (Dep't of Mechanical Engineering, Graduate School, Yonsei University)
Choi, Ha-Young (High-speed Railroad Systems Research Center, KRRI)
Publication Information
Journal of Ocean Engineering and Technology / v.26, no.6, 2012 , pp. 80-85 More about this Journal
Abstract
The methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) were implemented in the present study. RBRDO is an integrated method that accounts for the design robustness of an objective function and for the reliability of constraints. The objective function in RBRDO is expressed in terms of the mean and standard deviation of an original objective function. Thus, a multi-objective formulation is employed. The regressive approximate models are generated via the moving least squares method (MLSM) and constraint-feasible moving least squares method (CF-MLSM), which make it possible to realize the feasibility regardless of the multimodality/nonlinearity of the constraint function during the approximate optimization processes. The regression model based RBRDO is newly devised and its numerical characteristics are explored using the design of an actively controlled ten bar truss structure.
Keywords
Reliability based design optimization; Robust optimization; Reliability based robust design optimization; Conservative approximation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Breitkopf, P., Rassineux, A., Villon, P., 2002. An introduction to moving least squares meshfree methods. Revue Europenne des Elements Finis 11, 825-868.   DOI
2 Buskensa. C., Maurer. H., 2000. SQP-methods for solving optimal control problems with control and state constraints: adjoint variables, sensitivity analysis and real-time control. Journal of Computational and Applied Mathematics, 120, 85-108.   DOI   ScienceOn
3 Chun, H.Y., Min, S., 2005. Comparative Studies of Reliability- Based Topology Optimization. Proceedings of Fall Annual Meeting of KSME, 812-817.
4 Joung, T.H., Nho, I.S., Lee, J.H., Han, S.H., 2005. Design Optimization of a Deep-sea Pressure Vessel by Reliability Analysis. Journal of Ocean Engineering and Technology, 19(2), 40-46.
5 Lee, D.H., Min, S.J., Kim, S.D., 2003. Optimal Design of Rubble Mound Breakwater Used by Partial Safety Factor Method. Journal of Ocean Engineering and Technology, 17(6), 23-31.
6 Lee, J., Hajela, P., 1997. GAs in Decomposition Based Design- Subsystem Interactions Through Immune Network Simulation. Structural Optimization, 14, 248-255.   DOI   ScienceOn
7 Lee, K.H., Park, G.J., 2001. Robust Optimization Considering Tolerances of Design Variables. Computers and Structures, 79(1), 77-86.   DOI   ScienceOn
8 Ryu, C.H., Lee, J.H., Yoon, J.S., 2007. An Algorithm on Determination of Process Parameters for Roller Bending of Curved Shell Plates. Journal of the Society of Naval Architects of Korea, 44(5), 517-525.   과학기술학회마을   DOI   ScienceOn
9 Sandgren, E., Cameron, T.M., 2002. Robust design optimization of structures through consideration of variation. Computers and Structures, 80, 1605-1613.   DOI   ScienceOn
10 Song, C.Y., Lee J., 2009. Strength Design of Knuckle Component Using Moving Least Squares Methods. Proc. IMechE, Part D: Journal of Automobile Engineering, 223(8), 1019- 1032.   DOI   ScienceOn
11 Song, C.Y., Lee J., Choung, J., 2011. Reliability-based design optimization of an FPSO riser support using moving least squares response surface meta-models. Ocean Engineering, 38, 304-318.   DOI   ScienceOn
12 Tu, J., Choi, K.K., Park, Y.H., 1999. A new study on reliability- based design optimization. Journal of Mechanical Design, 121(4), 557-564.   DOI   ScienceOn
13 Youn, B.D., Choi, K.K., 2004. A new response surface methodology for reliability-based design optimization. Computers and Structures, 82(2), 241-256.   DOI   ScienceOn
14 Arora. J., 2004. Introduction to optimum design. 2nd Edition, McGraw-Hill, New York.