Artificial Neural Network Model for Prediction of Liquefaction Potential in Soil Deposits

With the increase in population, the evaluation of liquefaction is becoming more important for land use planning and development. In soil deposits under undrained condition, earthquakes induce cyclic shear stresses, may lead to soil liquefaction. Artificial neural network (ANN) is one of the, artificial intelligence (AI) approaches that can be classified as machine learning. Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. In order to address the collective knowledge built up in conventional liquefaction engineering, an alternative general regression neural network model is proposed in this paper. To meet this objective, a total of 30 boreholes are introduced into the model. The data includes the results of field test from (Babol, Mazandaran, Iran). The results produced by the proposed Artificial Neural Network model compared well with the determined liquefaction decision obtained by simplified methods. It provides a viable liquefaction potential assessment tool that assist geotechnical engineers in making an accurate and realistic predictions. Furthermore, this study integrates knowledge learned from field test and seismic parameters to the ongoing development of liquefaction analysis. The results show that there is liquefaction potential in western part of Babol, and in southern part of Babol no liquefaction potential were seen. In middle part and eastern part low liquefaction potential were predicted by ANNs. This study shows that neural networks are a powerful computational tool which can analyze the complex relationship between soil liquefaction potential and effective parameters in liquefaction

Investigation of Bearing Capacity and Settlement of Strip Footing on Clay Reinforced with Stone Columns

Abstract: A method is proposed for evaluating settlement and bearing capacity of soft clay that reinforced with stone columns. A numerical analysis was carried out using Plaxis software with considering the effect of compaction of soft clay. For the numerical simulation, Mohr-Coulomb model was considered for the soft soil, sand and stone column. From numerical results, the bearing capacity ratio(BCR) and settlement reduce ratio(SRR) of the soil has been estimated. On the bases of the analysis performed in this research, it can be concluded that the value of BCR is depended on footing width. The results are compared with those available in the literature and the advantages of the numerical analysis were highlighted

Empirical correlations of shear wave velocity (Vs) and standard penetration resistance based on soil type in Babol city

1566-1577Shear wave velocity (Vs) plays a fundamental role in soil dynamic problems and seismic analyses to estimate the site effect for earthquake geotechnical microzonation. During an earthquake the ground motion is significantly affected by the soil type, stiffness and geological condition. The shear wave velocity and Shear modulus are the applied variables in nonlinear site response analysis. As a part of microzonation study for the Babol city a total of 35 boreholes have been drilled in 35 km2 of the research area. The depths of these boreholes ranged about 25 to 30 m. SPT blow counts were taken in each 2 m depth. Many geophysical surveys, and generally 35 downhole logging surveys, are carried out in 35 mentioned boreholes for generation and measurement of shear waves in situ. According to the results of various in-situ tests, the variation of shear wave velocity obtained by downhole tests and SPT-N values were studied and some correlations were developed. It can be said that the developed correlations show acceptable prediction performance and can be used for similar geotechnical and geological site conditions

Microzonation of Liquefaction Hazard using Liquefaction Index in Babol City

Liquefactio

Liquefaction assessment by microtremor measurements in Babol city

The recent researchers have discovered microtremor applications for evaluation of the liquefaction potential. Microtremor measurement is a fast, applicable and cost-effective method with extensive applications. In the present research the liquefaction potential has been reviewed by utilization of microtremor measurement results in Babol city. By using the fundamental frequency and amplification factor, the value of vulnerability index (Kg) was calculated and the liquefaction potential has been evaluated. For controlling the accuracy of this method, its output has compared with the results of Seed and Idriss method in 30 excavated boreholes within the study area. These two methods show an acceptable conformity with each other. Also, the artificial neural network (ANN) with different inputs was trained. Regarding the results of the three methods, we can conclude the threshold value of liquefaction potential is Kg=5. By reviewing and comparing these three methods, it will be observed that microtremors have the capability of assessing the liquefaction potential with desirable accuracy