Errors and uncertainties in probabilistic engineering analysis

Abstract

The developing field of probabilistic design has matured to the point where several classes of analysis methods have been proven to be useful for engineering analysis of large high fidelity structures with uncertain parameters. However, several barriers still stand in the way of widespread acceptance of probabilistic methods into the design practice. These include lack of data for characterizing probabilistic inputs, lack of understanding of analysis methodologies and associated limitations, lack of commercially available tools for performing probabilistic analysis, and lack of verification and validation examples. As a first step towards developing more computationally robust tools for performing probabilistic analysis and improving user understanding of analysis assumptions and limitations, this paper identifies the various types of error that can be encountered when performing probabilistic analysis and offers some suggestions for mitigating or eliminating them from the analysis.

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