Journal
SOILS AND FOUNDATIONS
Volume 48, Issue 6, Pages 755-770Publisher
JAPANESE GEOTECHNICAL SOC
DOI: 10.3208/sandf.48.755
Keywords
artificial neural network; case history; cone penetration test; cyclic resistance ratio; cyclic stress ratio; earthquake; liquefaction potential; model; piezocone (IGC: C3/E8)
Funding
- U.S. Geological Survey (USGS), Department of the Interior under USGS [07HQGR0053]
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This paper presents a piezocone penetration test (CPTu) method for evaluating soil liquefaction potential covering a wider range of soil types than previous approaches and using simplified stress-based procedures. In the approach, the adjusted cyclic stress ratio is calculated with a recent formula created by Idriss and Boulanger, and the cyclic resistance ratio is determined as a function of both adjusted cone tip resistance (q(uN)) and soil behavior type index (I-c). The new method is established through artificial neural network learning of documented cases. One unique feature of this method is the inclusion of excess porewater pressure ratio (B-q) in the formulation of Ic as per Jefferies and Davies. The proposed method is shown to be more applicable to a wider range of soils, including geomaterials that were previously considered too clay-rich to liquefy. The ability of this method to delineate liquefied cases from non-liquefied cases is clearly depicted with 3-D and 2-D graphs. Case studies of selected ground failure sites in Adapazari using the proposed method yield results that agree well with field observations in the 1999 Kocaeli earthquake.
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