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M Beer and P D Spanos (2005)
Simulation Based Structural Reliability Assessment Involving Imprecise Data
In: Safety and Reliability of Engineering Systems and Structures Proceedings of the 9th Int. Conference on Structural Safety and Reliability, edited by G. Augusti and G.I. Schuëller and M. Ciampoli. Millpress, Rotterdam, pages 1725--1732.
In this paper a new sampling method for probabilistic safety assessment of structures involving imprecise data is presented. This method is formulated as sample-induced simulation technique and aims at combining the benefits of established simulation methods like Monte-Carlo simulation with those of models with imprecise data. In this regard an approach is pursued to overcome certain weaknesses of current methods. First, the specification of probability distributions on the basis of frequently small samples is circumvented. All information contained in a given sample is accounted for directly and without estimating probability distribution functions explicitly. Second, uncertainty in sample elements is taken into account. As no probability distributions are required, the considerable numerical cost of evaluating samples comprising imprecise data is eliminated. Examples demonstrate the capability of the sample-induced simulation technique for dealing with both real-valued data and imprecise data.
