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An Earthquake-Induced Reinforced Slope Sliding Displacement Estimation Model Using a Probabilistic Procedure
https://orcid.org/http://orcid.org/0000-0002-8264-0540
https://orcid.org/http://orcid.org/0000-0002-1927-7793
https://orcid.org/http://orcid.org/0000-0001-9144-2717
This study proposed a model for predicting the probabilistic sliding displacement of geosynthetic-reinforced soil slopes. A numerical simulation was illustrated as an example to calculate the seismic displacement based on three types of Newmark analysis. A synthetic dataset including 972 numerical simulations was generated for statistical analysis by data derived from real-time strong-ground motions of 30 worldwide earthquakes. An investigation into the relationship between reinforced slope properties and motion characteristics was performed using a parametric analysis. It was concluded that coupled analysis calculated higher values for the earthquake-induced sliding displacement of geosynthetic-reinforced soil slopes. In addition, the probabilistic assessment indicated that soil friction angle is more influential on sliding displacement than the other random variables. A cumulative distribution function was constructed for estimating probabilistic seismic displacement based on 5000 Latin-hypercube sampling.
An Earthquake-Induced Reinforced Slope Sliding Displacement Estimation Model Using a Probabilistic Procedure
https://orcid.org/http://orcid.org/0000-0002-8264-0540
https://orcid.org/http://orcid.org/0000-0002-1927-7793
https://orcid.org/http://orcid.org/0000-0001-9144-2717
This study proposed a model for predicting the probabilistic sliding displacement of geosynthetic-reinforced soil slopes. A numerical simulation was illustrated as an example to calculate the seismic displacement based on three types of Newmark analysis. A synthetic dataset including 972 numerical simulations was generated for statistical analysis by data derived from real-time strong-ground motions of 30 worldwide earthquakes. An investigation into the relationship between reinforced slope properties and motion characteristics was performed using a parametric analysis. It was concluded that coupled analysis calculated higher values for the earthquake-induced sliding displacement of geosynthetic-reinforced soil slopes. In addition, the probabilistic assessment indicated that soil friction angle is more influential on sliding displacement than the other random variables. A cumulative distribution function was constructed for estimating probabilistic seismic displacement based on 5000 Latin-hypercube sampling.
An Earthquake-Induced Reinforced Slope Sliding Displacement Estimation Model Using a Probabilistic Procedure
https://orcid.org/http://orcid.org/0000-0002-8264-0540
https://orcid.org/http://orcid.org/0000-0002-1927-7793
https://orcid.org/http://orcid.org/0000-0001-9144-2717
This study proposed a model for predicting the probabilistic sliding displacement of geosynthetic-reinforced soil slopes. A numerical simulation was illustrated as an example to calculate the seismic displacement based on three types of Newmark analysis. A synthetic dataset including 972 numerical simulations was generated for statistical analysis by data derived from real-time strong-ground motions of 30 worldwide earthquakes. An investigation into the relationship between reinforced slope properties and motion characteristics was performed using a parametric analysis. It was concluded that coupled analysis calculated higher values for the earthquake-induced sliding displacement of geosynthetic-reinforced soil slopes. In addition, the probabilistic assessment indicated that soil friction angle is more influential on sliding displacement than the other random variables. A cumulative distribution function was constructed for estimating probabilistic seismic displacement based on 5000 Latin-hypercube sampling.
An Earthquake-Induced Reinforced Slope Sliding Displacement Estimation Model Using a Probabilistic Procedure
Transp. Infrastruct. Geotech.
Ghanbari, Ali (author) / Nazari, Reza A. (author) / Sharafi, Hassan (author)
2025-01-01
Article (Journal)
Electronic Resource
English
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