It is important in structural analysis and design, whether deterministic or
reliability-based, to know the level of uncertainty for the methods of strength prediction.
The uncertainty associated with strength prediction is the result of ambiguity and
vagueness in the system. This study addresses the ambiguity component of uncertainty;
this includes uncertainty due to randomness in the basic strength parameters (random
uncertainty) and systematic errors and scatter in the prediction of strength (modeling
uncertainty). The vagueness component is briefly discussed.
A methodology for quantifying modeling and random uncertainty is presented for
structural failure modes with a well defined limit state. A methodology is also presented
for determining the relative importance of the basic strength parameters in terms of their
importance to the total random uncertainty. These methodologies are applied to the
compressive failure of longitudinally stiffened panels. The strength prediction model
used in this analysis was developed in the UK and is widely used in analysis and design.
Several experimental sample sets are used in the analysis. Mean values and coefficients
of variation are reported for the random and modeling uncertainties.
A comparison with results from other studies with several strength prediction
algorithms is undertaken for the modeling uncertainty. All of these studies involve
longitudinally stiffened panels which fail in axially compressive collapse. Ranges for the
mean and coefficient of variation of the modeling uncertainty are presented.
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