Dynamic equivalent soil characteristics identification using earthquake records

Techniques for soil property estimation can be categorized into two main groups, in-situ and laboratory methods. Previous investigations indicated that strong ground motions record provides a very useful tool to estimating the in-situ characteristics of soil. The main objective of the present work is to utilize the particle swarm optimization algorithm(PSOA) integrated with linear site response method to obtain the equivalent soil profile characteristics from the available surface and bedrock earthquake motion records. To demonstrate the numerical efficiency and the validity of this approach, the procedure is validated against an available case. Then this procedure is utilized to identify the soil properties profiles of the site by using strong ground motions data recorded during the Bam earthquake of December 26, 2003. The magnitude and PGA of Bam earthquake were MW 6.6 and 0.8 g respectively.     

Prediction of slope stability using artificial neural network (case study: Noabad, Mazandaran, Iran)

Investigations of failures of soil masses are subjects touching both geology and engineering. These investigations call the joint efforts of engineering geologists and geotechnical engineers. Geotechnical engineers have to pay particular attention to geology, ground water, and shear strength of soils in assessing slope stability. Artificial neural networks (ANNs) are very sophisticated modeling techniques, capable of modeling extremely complex functions. In particular, neural networks are nonlinear. In this research, with respect to the above advantages, ANN systems consisting of multilayer perceptron networks are developed to predict slope stability in a specified location, based on the available site investigation data from Noabad, Mazandaran, Iran. Several important parameters, including total stress, effective stress, angle of slope, coefficient of cohesion, internal friction angle, and horizontal coefficient of earthquake, were used as the input parameters, while the slope stability was the output parameter. The results are compared with the classical methods of limit equilibrium to check the ANN model’s validity.     

Settlement evaluation of soft clay reinforced with stone columns using the equivalent secant modulus

A method is proposed to evaluate settlement of soft clay reinforced with stone columns. Finite element analyses were carried out using 15-noded triangular elements with PLAXIS. A drained analysis was carried out using Mohr?CCoulomb??s criterion for soft clay, stones, and sand. The stress due to column installation has been considered in the analysis. At the interface between the stone column and soft clay, interface elements have been used. The settlement ratio (SR) of the soil has been estimated using the equivalent secant modulus. The results are compared with those available in the literature, and the advantages of the numerical analysis were highlighted. Based on the results of this analysis, the SR decrease with compaction surrounding soft soil, but decrease of SR is mainly due to a stiffer column material in soft clay.