Suitability assessment of the best liquefaction analysis procedure based on SPT data

At present, there exist many methods for liquefaction analysis of a soil deposit. Some of them are suitable for only coarse grained soils, while a few others can also evaluate the liquefaction potential of both fine-and coarse-grained soils. It is important to identify the most suitable method for liquefaction analysis. The current study looks at measuring soil's liquefaction potential using various methods such as Seed (ASCE J Soil Mech Found Div 97:1249-1273, 1971), Toprak et al. (CPT-and SPT-based probabilistic assessment of liquefaction potential. In: 7th US-Japan Workshop on Earthquake Resistant Design of Lifeline Facilities and Countermeasures against Liquefaction, Seattle. Multidisciplinary Center for Earthquake Engineering Research Buffalo, NY, p 18,1999), and Idriss and Boulanger (Soil Dyn Earthq Eng 26:115-130, 2006). The main objective of this study is to identify the most suitable method for liquefaction analysis based on factor of safety and Performance Fitness Error Metrics (PFEMs), Rank analysis, Gini index, etc. The contribution of various independent variables, such as corrected SPT N values, fine content, maximum horizontal ground acceleration, total vertical stress, total effective stress, magnitude moment, and depth below ground level towards the evaluated liquefaction potential and probability of liquefaction has been assessed through the use of Gini Index (GI). The computed probability of liquefaction (PL) values are compared with the given liquefaction status of case history data using Performance Fitness Error Metrices. Performance Fitness Error Metrics for the Idriss and Boulanger (2006) method are found to be higher than those for Toprak et al. (1999) and Seed and Idriss (ASCE J Soil Mech Found Div 97:1249-1273) methods. Based on these PFEMs, it is found that the Idriss and Boulanger (2006) methods of liquefaction analysis at any site are more accurate than the other two methods. It is observed that Idriss and Boulanger (2006) method gives the highest rate of successful prediction percentage of correctly predicted liquefied and non-liquefied cases.