A generalized separation for the variance contributions of input variables and their distribution parameters

For the structural system with both the uncertainties of input variables and their distribution parameters, this work investigates the generalized separation approach by transforming the original variable into the auxiliary variable with arbitrary distribution. Based on the variance based sensitivity analysis, the generalized sensitivity measures can be given, which are used to identify the influences of the auxiliary variables and distribution parameters simultaneously. For the different auxiliary variables, the variance contributions are proved to be identical, which illustrates the correctness of the generalized separation approach. Then the relationship of the variance contributions of original variables with those of the auxiliary variables and distribution parameters is investigated. Several examples are employed to demonstrate the rationality of the generalized separation approach.