جستجوی مقالات مرتبط با کلیدواژه « reliability-based optimization » در نشریات گروه « مکانیک »

This competitive commercial space forces designers and manufactures to produce and supply products with high quality and low prices at a desirable level of reliability. On the other hand, during the design and production process, engineers are always faced with uncertainty. In recent years, to encounter these uncertainties and guarantee the quality and reliability of a system subsequently, reliability-based robust design optimization (RBRDO) algorithms have been developed based on robust design optimization (RDO) and reliability-based optimization (RBDO). In practical engineering, uncertainties of some design parameters or variables are epistemic and only a few samples are available for designer. Generally, some of the RBRDO methods ignore the information in the design process. This approach can lead to an enormous error. Other RBRDO methods ignore this valuable information in the design process. This study, a comprehensive RBRDO framework is developed by combining Bayesian reliability analysis and dimensionality reduction method (DRM) using NSGA2-II multi-objective optimization algorithm. For verification of the proposed algorithm, an engineering example is selected and the effects of epistemic uncertainty on objectives are studied. Moreover, the results of the proposed approach are compared with other existing approaches at a specific case of available data about epistemic uncertainty.

This article presents an efficient reliability-based optimization method for critical structural design, in which, the probability of failure (Pf) should remain in a small bound. Critical structures should be designed to be optimal and reliable. Despite significant progress in reliability and optimization techniques, their interaction, which is considered in reliability-based optimization (RBDO), is faced with several challenges, especially in reliability analysis of critical constraints (constraints with Pf less than 10-5). To address this issue, in this paper the cross-entropy method is intended for reliability analysis and is combined with Genetic Algorithm in a double-loop framework to implement RBDO. The cross-entropy method is based on Monte Carlo simulation, except that the variance of sampling is reduced, which leads to a faster and more accurate reliability analysis method. The proposed RBDO method is demonstrated on two structural design. The obtained results show a high capability in reliability-based optimization of critical structures. In addition, using the proposed method, in comparison with traditional safety factor method, provides a more substantial manner in reliability improvement.