Volume 11, Number 2 and B (Transaction B: Geotechnical Engineering 2013) | IJCE 2013, 11(2 and B): 100-111 | Back to browse issues page


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Baziar M H, Saeedi Azizkandi A. Evaluation of lateral spreading utilizing artificial neural network and genetic programming. IJCE. 2013; 11 (2) :100-111
URL: http://ijce.iust.ac.ir/article-1-820-en.html

Abstract:   (2147 Views)

Due to its critical impact and significant destructive nature during and after seismic events, soil liquefaction and liquefactioninduced

lateral ground spreading have been increasingly important topics in the geotechnical earthquake engineering field

during the past four decades. The aim of this research is to develop an empirical model for the assessment of liquefaction-induced

lateral ground spreading. This study includes three main stages: compilation of liquefaction-induced lateral ground spreading

data from available earthquake case histories (the total number of 525 data points), detecting importance level of seismological,

topographical and geotechnical parameters for the resulted deformations, and proposing an empirical relation to predict

horizontal ground displacement in both ground slope and free face conditions. The statistical parameters and parametric study

presented for this model indicate the superiority of the current relation over the already introduced relations and its applicability

for engineers.

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Type of Study: Research Paper | Subject: Seismic Geotechnique

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