Abstract
Degradation failure is one of the main reasons for complex mechanical systems losing their functions. Research on multidisciplinary design optimization under uncertainties should shift from static uncertainties to time-varying uncertainties. Aiming at time-varying uncertainties in mechanical systems, we put forward a multidisciplinary reliability design optimization method using stochastic process theory. First, we investigated the characteristics of time-varying uncertainties in complex mechanical systems, and then utilized stochastic process theory to quantify time-varying uncertainties. Second, through combining the multidisciplinary simultaneous analysis and design optimization method, the model of multidisciplinary design optimization under time-varying uncertainties is established. Moreover, a mathematical problem and an engineering example are provided to illustrate the accuracy and effectiveness of the proposed method.
Highlights
Multidisciplinary design optimization (MDO) of complex mechanical systems has shown wide application recently.[1,2,3,4] Increasing attentions are being paid on MDO under uncertainties in recent years
Gu et al.[7] derived limit expression of uncertainty propagation based on Taylor series method, and built stochastic uncertainty analysis model
Research methods to deal with aleatory and epistemic uncertainties in MDO may largely improve the reliability of complex systems, these research methods cannot accurately describe the sources, essential characteristics, and propagation properties of time-varying uncertainties and School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu, P.R
Summary
Multidisciplinary design optimization (MDO) of complex mechanical systems has shown wide application recently.[1,2,3,4] Increasing attentions are being paid on MDO under uncertainties in recent years. Keywords Multidisciplinary design optimization, time-varying uncertainty, stochastic process, time-varying reliability model, simultaneous analysis and design Veneziano et al.[17] assumed that time-varying uncertainties are Gauss distributions and proposed a system reliability analysis method.
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