Department of Civil and Environmental Engineering, Shiraz University of Technology, Shiraz, Iran
Computational Geomechanics Group, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK
During earthquake seismic waves propagate vibrations that carry energy from the source of the shaking outwards. Seismic waves can be distinguished by the velocity and shape of propagation. The velocity of waves depends on the elastic properties and density of the soil layers through which the waves pass. Probabilistic analysis of earthquake waves can be used as an effective tool to evaluate inherent uncertainty in the soil properties and the resulting uncertainty in site classification. In this research the jointly distributed random variables method is used for probabilistic analysis and reliability assessment of shear wave velocityrelationship. The selected stochastic parameters are density, elastic modules and Poisson's ratio which are modeled using truncated normal probability distribution functions. The results are compared with the Monte Carlo simulation, point estimated method and first order second moment method. Comparison of the results indicates very good performance of the proposed approach for assessment of reliability. It is shown that this method can correctly predict the influence of stochastic input parameters and capture the expected probability distribution of shear wave velocity correctly. It is also shown that the modulus of elasticity is the most effective parameter in shear wave velocity.