Random model with fuzzy distribution parameters for hybrid uncertainty propagation in engineering systems

摘要

As a typical method for hybrid uncertainty analysis, imprecise probability theory recently plays an increasing important role in many engineering systems. To extend its application, this paper proposes a new imprecise probability model and a more efficient numerical method for hybrid uncertainty propagation. Instead of crisp real values, fuzzy sets with membership functions are utilized to describe the epistemic uncertainty in the distribution parameters of input random variables. In the presence of fuzzy distribution parameters, the conventional random moments of output response will include certain fuzzy characteristic. Based on the cut-set operation and fuzzy decomposition theorem, the calculation of fuzzy random moment can be transformed into a series of lambda-cut interval random moments. To further decrease the huge computational cost caused by the original complex computational model, a relatively simple metamodel with explicit expression is constructed by the radial basis functions. Meanwhile, the bisection points with nestedness property are adopted as the experimental design strategy. Finally, two examples are implemented to verify the effectiveness of the proposed model and method in practical application. (C) 2019 Elsevier B.Y. All rights reserved.