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Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading
Joint Authors
Ma, Jianlin
Yang, Yanxin
Yang, Bai
Su, Chunhui
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-07
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The residual shear strength of liquefied soil is critical to estimating the displacement of lateral spreading.
In the paper, an Artificial Neural Network model was trained to predict the residual shear strength ratio based on the case histories of lateral spreading.
High-quality case histories were analyzed with Newmark sliding block method.
The Artificial Neural Network model was used to predict the residual shear strength of liquefied soil, and the post-liquefaction yield acceleration corresponding with the residual shear strength was obtained by conducting limit equilibrium analysis.
Comparing the predicted residual shear strength ratios to the recorded values for different case histories, the correlation coefficient, R, was 0.92 and the mean squared error (MSE) was 0.001 for the predictions by the Artificial Neural Network model.
Comparison between the predicted and reported lateral spreading for each high-quality case history was made.
The results showed that the probability of the lateral spreading calculated with the Newmark sliding block method using the residual shear strength was 98% if a lateral spreading ratio of 2.0 was expected and a truncated distribution was used.
An exponential relationship was proposed to correlate the residual shear strength ratio to the equivalent clean sand corrected SPT blow count of the liquefied soil.
American Psychological Association (APA)
Yang, Yanxin& Yang, Bai& Su, Chunhui& Ma, Jianlin. 2020. Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1125353
Modern Language Association (MLA)
Yang, Yanxin…[et al.]. Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading. Advances in Civil Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1125353
American Medical Association (AMA)
Yang, Yanxin& Yang, Bai& Su, Chunhui& Ma, Jianlin. Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1125353
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1125353