Reliability-Based Design Optimization under Stationary Stochastic Process Loads
Time-dependent reliability-based design ensures the satisfaction of reliability requirements for a given period of time, but with a high computational cost. This work improves the computational efficiency by extending the sequential optimization and reliability analysis (SORA) method to time-dependent problems with both stationary stochastic process loads and random variables. The challenge of the extension is the identification of the most probable point (MPP) associated with time-dependent reliability targets. Since a direct relationship between the MPP and reliability target does not exist, this work defines the concept of equivalent MPP, which is identified by the extreme value analysis and the inverse saddlepoint approximation. With the equivalent MPP, the time-dependent reliability-based design optimization is decomposed into two decoupled loops: deterministic design optimization and reliability analysis, and both are performed sequentially. Two numerical examples are used to show the efficiency of the proposed method.
Z. Hu and X. Du, "Reliability-Based Design Optimization under Stationary Stochastic Process Loads," Engineering Optimization, vol. 48, no. 8, pp. 1296-1312, Taylor & Francis, Aug 2016.
The definitive version is available at https://doi.org/10.1080/0305215X.2015.1100956
Mechanical and Aerospace Engineering
Intelligent Systems Center
Keywords and Phrases
Computational efficiency; Design; Efficiency; Inverse problems; Machine design; Numerical methods; Optimization; Random processes; Reliability; Stochastic systems; Extreme value analysis; Reliability requirements; Reliability-based design optimization; Saddle-point approximation; Sequential optimization; Stationary stochastic process; Time dependent reliability; Time-dependent problem; Reliability analysis
International Standard Serial Number (ISSN)
Article - Journal
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01 Aug 2016