Reliability based design optimization with experiments on demand
2012 (English)Report (Other academic)
In this paper, an algorithm for reliability based design optimization (RBDO) is presented. It incorporates a novel procedure in which experiments are performed one at a time where and when they are needed. The procedure is called experiments on demand. The experiment procedure utilizes properties specific to RBDO and the problem at hand augmented by the concept of D-optimality familiar from traditional design of experiments. Furthermore, an adaptive surrogate model fitting scheme is proposed which balances numerical stability and convergence rate as well as accuracy. Benchmarked against algorithms in the literature, the number of experiments needed for convergence was reduced by up to 80 % for a frequently used analytical problem and by up to 19 % for an application example. The accuracy of the reliability index is in line with the most efficient algorithm against which it was benchmarked but up to 3 % lower than the most accurate algorithm.
Place, publisher, year, edition, pages
2012. , 13 p.
Trita-HFL, ISSN 1104-6813 ; 519
Experiments on demand, Reliability based design optimization, Surrogate model
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-90800OAI: oai:DiVA.org:kth-90800DiVA: diva2:506559
QC 201202292012-02-292012-02-292012-03-01Bibliographically approved