A study of the liquefaction risk potential at Yuanlin, Taiwan

Abstract

The method by Iwasaki et al. [Iwasaki, T., Arakawa, T., Tokida, K., 1982. Simplified procedures for assessing soil liquefaction during earthquakes. Proceedings of the Conference on Soil Dynamics and Earthquake Engineering, Southampton, UK, pp. 925–939] for evaluating the liquefaction failure potential is widely used in Japan, Taiwan, and other countries due to its ease of use and general applicability. In this method, an index, called the Liquefaction Potential Index ( I L), is calculated based on an integration of the calculated factor of safety ( F s) over depth with a weighting function. Iwasaki et al. (1982) provided a set of criteria to interpret the calculated index I L based on a calibration with his dataset of field performance cases. However, in their method, the factor of safety ( F s) is based on the liquefaction evaluation method adopted in the Japanese Highway Bridge Design Code [JSHE, 1990. Highway Bridge Design Guide Book. Japan Society of Highway Engineering, in Japanese]. Whether other liquefaction evaluation methods can be used in conjunction with the index I L or not needs further investigation. In this paper, the Cone Penetration Test (CPT) data from Yuanlin, Taiwan, the area that suffered the most from liquefaction in the 1999 Chi-Chi, Taiwan, earthquake, are analyzed. Three CPT-based methods are used for the calculation of the factor of safety for these cases derived from the Chi-Chi earthquake. These factors of safety are used to define the liquefaction potential and risk indexes. The calculated indexes are then used to construct the failure potential maps, and these maps are checked with the field observations. The study shows that the Liquefaction Risk Index ( I R) defined in conjunction with the Juang et al. [Juang, C.H., Yuan, H., Lee, D.H., Lin, P.S., 2003. Simplified CPT-based method for evaluating liquefaction potential of soils. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, vol. 129, no. 1, pp. 66–80] method yields the best result in interpreting field observations.