An Improved Multidimensional Parallelepiped Model for Structural Uncertainty Analysis
The multidimensional parallelepiped model is a non-probabilistic convex set model that can take into account dependent and independent variables simultaneously.Therefore,it is more suitable for the"multi-source uncertainty"problems in engineering structures.An improved multidimensional parallelepiped model is presented to more reasonably and efficiently quantify the structural uncertainties.An explicit expression for the uncertainty domain of the parallelepiped model is given by defining the correlation angle and marginal intervals of interval variables.A method is further formulated to construct a multidimensional parallelepiped model based on the experimental sample points.The analyzed results of three numerical examples show that the proposed model can better reflect the correlation of interval variables,and has a more compactness and rationality than the traditional multidimensional parallelepiped model.
multidimensional parallelepiped modelnon-probabilistic convex set modelcorrelation of variablesexplicit expression of uncertainty domain
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