Abstract
Uncertainties are inherent in any structural system. Traditional design optimization techniques consider uncertainties implicitly by partial safe factors. However, Reliability-Based Design Optimization (RBDO) methods account for uncertainties explicitly. These methods find an optimum design that verifies several reliability constraints. The objective here is to obtain an economic and safe design. This paper describes several RBDO methods and the functions programmed to implements these methods. These functions form a package added to the well known Structural Reliability Toolbox Finite Element Reliability Using Matlab (FERUM). A structural example has been solved with the functions implemented: a transmission tower truss.
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References
Lee, T.W., Kwak, B.M.: A Reliability-Based Optimal Design Using Advanced First Order Second Moment Method. Mech. Struct. Mach. 15(4), 523–542 (1987-1988)
Tu, J., Choi, K.K.: A New Study on Reliability Based Design Optimization. Journal Mechanical Design ASME 121(4), 557–564 (1999)
Youn, B.D., Choi, K.K., Park, Y.H.: Hybrid Analysis Method for Reliability-Based Design Optimization. Journal of Mechanical Design, ASME 125(2), 221–232 (2003)
Youn, B.D., Choi, K.K., Du, L.: Adaptive probability analysis using an enhanced hybrid mean value (HMV+) method. Journal of Structural and Multidisciplinary Optimization 29(2), 134–148 (2005)
Youn, B.D., Choi, K.K., Du, L.: Enriched Performance Measure Approach (PMA+) for Reliability-Based Design Optimization Approaches. AIAA Journal 43(4), 874–884 (2005)
Du, X., Chen, W.: Sequential optimization and reliability assessment method for efficient probabilistic design. ASME J. Mechanical Design 126(2), 225–233 (2004)
Chen, X., Hasselman, T.K., Neill, D.J.: Reliability based structural design optimization for practical applications. In: Proceedings, 38th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibit, Orlando, FL (1997)
Kuschel, N., Rackwitz, R.: A new approach for structural optimization of series systems. In: Melchers, R.E., Stewart, M.G. (eds.) Applications of Statistics and Probability, pp. 987–994. Balkema, Rotterdam (2000)
Liang, J., Mourelatos, Z.P., Tu, J.: A single loop method for reliability based design optimization. In: Proceedings of the 30th ASME Design Automation Conference, Salt Lake City, UT, Paper nº DETC 2004/DAC-57255 (September 2004)
Wang, L., Kodiyalam, S.: An efficient method for probabilistic and robust design with non-normal distributions. In: Proceedings of 34rd AIAA SDM Conference. Denver, CO (2002)
Agarwal, H., Renaud, J., Lee, J., Watson, L.: A unilevel method for reliability based design optimization. In: 45th AAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Material Conference, Palm Springs, CA (2004)
Streicher, H., Rackwitz, R.: Time-variant reliability-oriented structural optimization and a renewal model for life-cicle costing. Probabilistic Engineering Mechanics 19(1-2), 171–183 (2004)
Liang, J., Mourelatos, Z.P., Tu, J.: A single-loop method for reliability-based design optimization. Int. J. Product Development 5(1-2), 76–92 (2008)
Aoues, Y., Chateauneuf, A.: Benchmark study of numerical methods for reliability-based design optimization. Journal of Structural and Multidisciplinary Optimization 41, 277–294 (2010)
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Celorrio Barragué, L. (2012). Development of a Reliability-Based Design Optimization Toolbox for the FERUM Software. In: Hüllermeier, E., Link, S., Fober, T., Seeger, B. (eds) Scalable Uncertainty Management. SUM 2012. Lecture Notes in Computer Science(), vol 7520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33362-0_21
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DOI: https://doi.org/10.1007/978-3-642-33362-0_21
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