Sequential Multidisciplinary Reliability Design and Optimization Based on Approximate Sensitivity Method under Random and Interval Uncertainties

doi:10.3901/JME.2015.21.174

Abstract

Abstract: To resolve the low computational efficiency problem of conventional reliability-based multidisciplinary design optimization (RBMDO), which is caused by the multi-source uncertainties and multi-nested loops during the design process of RBMDO. A new mixed uncertainties multidisciplinary design optimization (MUMDO) method is proposed by integrating the approximate sensitivity technique, bi-level integrated system synthesis strategy and performance measure approach, which can deal with both random and interval uncertainties simultaneously. The MUMDO model is formulated based on a new proposed reliability evaluation index and the mixed uncertainties quantification method using the probability theory and convex model. The approximate sensitivity information is employed to replace the real sensitivity value during the MUMDO, avoiding a large number of iterations of sensitivity calculations in each cycle. In addition, the four-layered nested MUMDO flowchart has been decoupled into a series of sequential execution of multidisciplinary design optimization and multidisciplinary reliability analysis based on the sequential optimization and reliability assessment (SORA). As a result, it is not necessary to evaluate the whole reliability model in each cycle, and a great number of sensitivity analysis and multidisciplinary analysis iterations are eliminated. Taking a vehicle side impact design as an example, the results show that the proposed method can deal with the random and interval uncertainties simultaneously. And also, the efficiency of the proposed method has been improved by 10.98% and 23.63% respectively compared to that of conventional methods. Therefore, it is valuable in engineering design and optimization.

Key words: approximate sensitivity, multidisciplinary design optimization(MDO), performance measure approach, reliability analysis, mixed uncertainties

LIU Chengwu, LI Liansheng, QIAN Linfang. Sequential Multidisciplinary Reliability Design and Optimization Based on Approximate Sensitivity Method under Random and Interval Uncertainties[J]. Journal of Mechanical Engineering, 2015, 51(21): 174-184.

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