Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/43067
標題: Simplified cone penetration test-based method for evaluating liquefaction resistance of soils
作者: Juang, C.H.
林炳森
Yuan, H.M.
Lee, D.H.
Lin, P.S.
關鍵字: probability;statistics;earthquakes;liquefaction;cone penetration;tests;neural networks;fine-grained soils;cpt;reliability
Project: Journal of Geotechnical and Geoenvironmental Engineering
期刊/報告no:: Journal of Geotechnical and Geoenvironmental Engineering, Volume 129, Issue 1, Page(s) 66-80.
摘要: 
This paper presents a new simplified method for assessing the liquefaction resistance of soils based on the cone penetration test (CPT). A relatively large database consisting of CPT measurements and field liquefaction performance observations of historical earthquakes is analyzed. This database is first used to train an artificial neural network for predicting the occurrence and nonoccurrence of liquefaction based on soil and seismic load parameters. The successfully trained and tested neural network is then used to generate a set of artificial data points that collectively define the liquefaction boundary surface, the limit state function. An empirical equation is further obtained by regression analysis to approximate the unknown limit state function. The empirical equation developed represents a deterministic method for assessing liquefaction resistance using the CPT. Based on this newly developed deterministic method, probabilistic analyses of the cases in the database are conducted using the Bayesian mapping function approach. The results of the probabilistic analyses, expressed as a mapping function, provide a simple means for probability-based evaluation of the liquefaction potential. The newly developed simplified method compares favorably to a widely used existing method.
URI: http://hdl.handle.net/11455/43067
ISSN: 1090-0241
DOI: 10.1061/(asce)1090-0241(2003)129:1(66)
Appears in Collections:土木工程學系所

Show full item record
 

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.