A Fuzzy Logic Approach to Stochastic 1D Site Response Analysis accounting for Soil Uncertainties

Site response analysis, namely the analysis of the wave propagation of shear waves through a soil deposit, requires the specification of the input ground motion and the dynamic characterization of the soil deposit. While the stochastic approach is commonly used for modelling seismic excitation, the use of probability density functions for describing the soil properties is consistent only when precise informations based on a large amount of data from soil surveys are available. Conversely, a non-probabilistic approach based on fuzzy set theory would be more appropriate for dealing with uncertainties that are just expressed by vague, imprecise, qualitative, or incomplete information and supplied by engineering judgement. In this paper, a hybrid fuzzy-stochastic 1D site response analysis approach for dealing with soil uncertainties defined as convex normal fuzzy sets is addressed. Zadeh's extension principle, in combination with an efficient implementation of the Differential Evolution Algorithm is used for global minimization and maximization. Results are presented as fuzzy median value ofthe largest peaks of the peak ground acceleration at the surface by considering four types of soil classified in accordance with the European seismic building code.