Artificial Neural Network Model for Evaluating Gravelly Soils Liquefaction Using Shear Wave Velocity: Fid-Bau Portal

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Artificial Neural Network Model for Evaluating Gravelly Soils Liquefaction Using Shear Wave Velocity

Kang, F. / Li, J. J. / Zhou, H.

Evaluation of liquefaction potential of soil is important in geotechnical earthquake engineering. Significant phenomena of gravelly soil liquefaction in the 2008 Wenchuan earthquake were reported. Thus, further studies on the liquefaction potential of gravelly soil are needed. This paper investigates the potential of an artificial neural networks-based approach to assess the liquefaction potential of gravelly soils form actual shear wave velocity field data. The success rates for occurrence and non-occurrence of liquefaction cases in Wenchuan earthquake could be up to 100% and 94%, respectively. The study suggests that neural networks can successfully model the complex relationship between seismic parameters, soil parameters, and the liquefaction potential of gravelly soils.

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Artificial Neural Network Model for Evaluating Gravelly Soils Liquefaction Using Shear Wave Velocity

Kang, F. / Li, J. J. / Zhou, H.

Evaluation of liquefaction potential of soil is important in geotechnical earthquake engineering. Significant phenomena of gravelly soil liquefaction in the 2008 Wenchuan earthquake were reported. Thus, further studies on the liquefaction potential of gravelly soil are needed. This paper investigates the potential of an artificial neural networks-based approach to assess the liquefaction potential of gravelly soils form actual shear wave velocity field data. The success rates for occurrence and non-occurrence of liquefaction cases in Wenchuan earthquake could be up to 100% and 94%, respectively. The study suggests that neural networks can successfully model the complex relationship between seismic parameters, soil parameters, and the liquefaction potential of gravelly soils.

Artificial Neural Network Model for Evaluating Gravelly Soils Liquefaction Using Shear Wave Velocity

Kang, F. / Li, J. J. / Zhou, H.

Evaluation of liquefaction potential of soil is important in geotechnical earthquake engineering. Significant phenomena of gravelly soil liquefaction in the 2008 Wenchuan earthquake were reported. Thus, further studies on the liquefaction potential of gravelly soil are needed. This paper investigates the potential of an artificial neural networks-based approach to assess the liquefaction potential of gravelly soils form actual shear wave velocity field data. The success rates for occurrence and non-occurrence of liquefaction cases in Wenchuan earthquake could be up to 100% and 94%, respectively. The study suggests that neural networks can successfully model the complex relationship between seismic parameters, soil parameters, and the liquefaction potential of gravelly soils.

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Title:

Artificial Neural Network Model for Evaluating Gravelly Soils Liquefaction Using Shear Wave Velocity

Contributors:

Kang, F. (author) / Li, J. J. (author) / Zhou, H. (author)

Conference:

Sixth China-Japan-US Trilateral Symposium on Lifeline Earthquake Engineering ; 2013 ; Chengdu, China

Published in:

International Efforts in Lifeline Earthquake Engineering ; 608-615

Publication date:

2013-12-11

ISBN:

9780784413234 , 9780784478073

DOI:

https://doi.org/10.1061/9780784413234.078

Type of media:

Conference paper

Type of material:

Electronic Resource

Language:

English

Keywords:

Seismic effects , Ground motion , Soil liquefaction , Shear waves , Earthquake engineering , Lifeline systems , Neural networks

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