Relative importance of uncertain structural parameters. Part I: algorithm |
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Authors: | H J Pradlwarter |
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Affiliation: | (1) Institute of Engineering Mechanics, Leopold-Franzens University, Technikerstr. 13, 6020 Innsbruck, Austria |
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Abstract: | A novel procedure for estimating the relative importance of uncertain parameters of complex FE model is presented. The method
is specifically directed toward problems involving high-dimensional input parameter spaces, as they are encountered during
uncertainty analysis of large scale, refined FE models. In these cases one is commonly faced with thousands of uncertain parameters
and traditional techniques, e.g. finite difference or direct differentiation methods become expensive. In contrast, the presented
method quickly filters out the most influential variables. Hence, the main objective is not to compute the sensitivity but
to identify those parameters whose random variations have the biggest influence on the response. This is achieved by generating
a set of samples with direct Monte Carlo simulation, which are closely scattered around the point at which the relative importance
measures are sought. From these samples, estimators of the relative importance are synthesized and the most important ones
are refined with a method of choice. In this paper, the underlying theory as well as the resulting algorithm is presented. |
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Keywords: | Uncertainty analysis Monte Carlo simulation Reliability Robust design Sensitivity analysis |
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