Reliability Based Shape Optimization of a Knuckle Component by using Sequential Linear Programming
2011 (English)Report (Other academic)
Deterministic successive response surface optimization is a most efficient tool for improving machine components. A possible drawback might be that the optimal design proposal is non-robust. For instance, a constraint on the von Mises stress mightn be violated for small changes in the optimal values of the design parameters. This might be checked after the optimization by performing robustness analysis. Another approach would be to replace the deterministic constraint on the von Mises stress with a probabilistic reliability constraint. This is the scope of the following paper. A sequential linear programming approach for reliability based design optimization is developed and implemented. The design variables are assumed to be normally distributed, where the standard deviations of the design variables can be given as coefficients of variation. A deterministic LP-problem is derived by performing a Taylor expansion of the constraint at the most probable point (MPP). The MPP is found by solving the optimality conditions using Newton’s method and the LP-problem is solved by an interior point method. The approach is efficient and robust. This is demonstrated by performing reliability based shape optimization of a real knuckle component to a heavy truck.
Place, publisher, year, edition, pages
2011. , 18 p.
JTH research report, ISSN 1404-0018 ; 2011:06
RBDO, SLP, MPP, Newton’s method
Reliability and Maintenance
IdentifiersURN: urn:nbn:se:hj:diva-16699OAI: oai:DiVA.org:hj-16699DiVA: diva2:456225