Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Assessment of Liquefaction Susceptibility of Fine-Grained Soil based on Soil Classification
https://orcid.org/http://orcid.org/0000-0002-4446-673X
Recent earthquakes point out that fine-grained soil having silt and clay also exhibits the behavior of liquefaction or cyclic mobility. Therefore, the present study is based on the liquefaction behavior of fine-grained considering soil classification criteria of the area which falls in high seismic regions of Bihar, India. The semi-empirical approach results are compared with the predicted results obtained from multiple linear regression (MLR) and artificial neural network considering significant in situ soil properties. It is observed that computational model outperforms the MLR model in the prediction of liquefaction potential of silty soil. Low-plasticity silts (ML) are showing lower liquefaction resistance as compared to intermediate-plasticity silts (MI) and high-plasticity silts (MH). It is found that liquefaction resistance increases with an increase in standard penetration test (SPT), blow count (N1)60, plasticity index and fine content. Based on Taylor’s diagram, the computational model is showing the highest prediction rate, outperforming all other approaches considered in the present study. Because of its accuracy, ease of use and time efficiency, it is an effective and reliable method for liquefaction prediction.
Assessment of Liquefaction Susceptibility of Fine-Grained Soil based on Soil Classification
https://orcid.org/http://orcid.org/0000-0002-4446-673X
Recent earthquakes point out that fine-grained soil having silt and clay also exhibits the behavior of liquefaction or cyclic mobility. Therefore, the present study is based on the liquefaction behavior of fine-grained considering soil classification criteria of the area which falls in high seismic regions of Bihar, India. The semi-empirical approach results are compared with the predicted results obtained from multiple linear regression (MLR) and artificial neural network considering significant in situ soil properties. It is observed that computational model outperforms the MLR model in the prediction of liquefaction potential of silty soil. Low-plasticity silts (ML) are showing lower liquefaction resistance as compared to intermediate-plasticity silts (MI) and high-plasticity silts (MH). It is found that liquefaction resistance increases with an increase in standard penetration test (SPT), blow count (N1)60, plasticity index and fine content. Based on Taylor’s diagram, the computational model is showing the highest prediction rate, outperforming all other approaches considered in the present study. Because of its accuracy, ease of use and time efficiency, it is an effective and reliable method for liquefaction prediction.
Assessment of Liquefaction Susceptibility of Fine-Grained Soil based on Soil Classification
https://orcid.org/http://orcid.org/0000-0002-4446-673X
Recent earthquakes point out that fine-grained soil having silt and clay also exhibits the behavior of liquefaction or cyclic mobility. Therefore, the present study is based on the liquefaction behavior of fine-grained considering soil classification criteria of the area which falls in high seismic regions of Bihar, India. The semi-empirical approach results are compared with the predicted results obtained from multiple linear regression (MLR) and artificial neural network considering significant in situ soil properties. It is observed that computational model outperforms the MLR model in the prediction of liquefaction potential of silty soil. Low-plasticity silts (ML) are showing lower liquefaction resistance as compared to intermediate-plasticity silts (MI) and high-plasticity silts (MH). It is found that liquefaction resistance increases with an increase in standard penetration test (SPT), blow count (N1)60, plasticity index and fine content. Based on Taylor’s diagram, the computational model is showing the highest prediction rate, outperforming all other approaches considered in the present study. Because of its accuracy, ease of use and time efficiency, it is an effective and reliable method for liquefaction prediction.
Assessment of Liquefaction Susceptibility of Fine-Grained Soil based on Soil Classification
Indian Geotech J
Kumar, Dilip (Autor:in) / Kumari, Sunita (Autor:in)
Indian Geotechnical Journal ; 54 ; 1366-1380
01.08.2024
15 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Assessment of Liquefaction Susceptibility of Fine-Grained Soil based on Soil Classification
| Springer Verlag | 2024
Assessment of the Liquefaction Susceptibility of Fine-Grained Soils
| British Library Online Contents | 2006
Assessment of the Liquefaction Susceptibility of Fine-Grained Soils
| Online Contents | 2006