Unified Reliability Measure Method Considering Uncertainties of Input Variables and Their Distribution Parameters

Aleatoric and epistemic uncertainties can be represented probabilistically in mechanical systems. However, the distribution parameters of are also uncertain due to sparsely available or inaccurate uncertainty information. Therefore, a unified reliability measure method that considers input variables their simultaneously is proposed. The information for could as result insufficient data interval information, which with evidence theory. probability density function constructed through fusing based on Gaussian interpolation algorithm, using weighted sum discrete parameters. index considering aleatoric calculated around most probable point. effectiveness proposed algorithm demonstrated comparison Monte Carlo engineering example crank-slider mechanism composite laminated plate.