On the uncertainty analysis of uplift capacity of suction caissons in clay based on the fuzzy sets theory

Abstract

Uncertainties in the input parameters of predictive models for uplift capacity of suction caisson lead to uncertain performance. To account for the influence of such uncertainties on the suction caisson stability, a fuzzy model is employed. The input uncertainties are introduced to the predictive formulas by triangular membership functions. To obtain the extreme values of the uplift capacity, optimization problems with many objectives are solved by the coupling of genetic algorithm (GA) with the uplift capacity estimation models. The relationships derived by different methods for the prediction of the uplift capacity, are analyzed by the fuzzy approach using a compiled database. Through the membership functions of several statistical measures, it is inferred that small input uncertainties can significantly affect the responses. Also, the recently proposed “M5-GP” - based prediction models are found to be vulnerable to input uncertainties, hence, a new revision called “Improved M5GP” model is developed. Finally, it is shown that the presented model is the best among various models regarding the reliability as well as the accuracy.