Modeling Uncertainty in Prediction of Pier Scour

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Abstract
Fuzzy regression is used to investigate the modeling uncertainty in the prediction of bridge pier scour. Fuzzy bias factors, which describe the bias between observed field data and scour estimates based on equations developed from laboratory data, were estimated. The bias exists because of the use of small-scale laboratory results to model large-scale, real-world problems. Fuzzy regression is a method of calibrating fuzzy numerical coefficients in a linear equation. Since the regression coefficients are fuzzy parameters, the output, in this case scour depth, is also a fuzzy number. The fuzzy bias factors developed from the fuzzy regression equations are compared for a variety of input data. The fuzzy bias factor provides useful information in the application of bridge pier scour equations currently available to engineers. The results of this study can be used by experimentalists in the interpretation of small-scale laboratory test results and by practicing engineers to adjust scour estimates.

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