Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Estimation of Uplift Capacity of Helical Pile Resting in Cohesionless Soil
https://orcid.org/http://orcid.org/0000-0001-6283-1588
In this research article, the finite element method was used to investigate the effect of embedment depth (H), friction angle (ɸ), the ratio of the diameter of the helical blade to the diameter of the shaft (Dp/Ds), number of helices (n), and inter-helix spacing ratio (S/Dp), on the uplift capacity of the helical pile (Qu). The helical pile was modeled and validated with the experimental results obtained from past investigations. The numerical data was then processed through an artificial neural network to develop a prediction model between the uplift capacity and varied parameters. An increment in Qu was observed with the increases in ϕ, n, H, and S/Dp. However, a decrease in Qu for single and double-helical piles was noted with an increase in Dp/Ds ratio. The outcome of the artificial neural network revealed that the best prediction of Qu was given by the SIGMOID activation function. Additionally, the sensitivity analysis showed that Qu was strongly influenced by S/Dp and least influenced by Dp/Ds ratio.
Estimation of Uplift Capacity of Helical Pile Resting in Cohesionless Soil
https://orcid.org/http://orcid.org/0000-0001-6283-1588
In this research article, the finite element method was used to investigate the effect of embedment depth (H), friction angle (ɸ), the ratio of the diameter of the helical blade to the diameter of the shaft (Dp/Ds), number of helices (n), and inter-helix spacing ratio (S/Dp), on the uplift capacity of the helical pile (Qu). The helical pile was modeled and validated with the experimental results obtained from past investigations. The numerical data was then processed through an artificial neural network to develop a prediction model between the uplift capacity and varied parameters. An increment in Qu was observed with the increases in ϕ, n, H, and S/Dp. However, a decrease in Qu for single and double-helical piles was noted with an increase in Dp/Ds ratio. The outcome of the artificial neural network revealed that the best prediction of Qu was given by the SIGMOID activation function. Additionally, the sensitivity analysis showed that Qu was strongly influenced by S/Dp and least influenced by Dp/Ds ratio.
Estimation of Uplift Capacity of Helical Pile Resting in Cohesionless Soil
https://orcid.org/http://orcid.org/0000-0001-6283-1588
In this research article, the finite element method was used to investigate the effect of embedment depth (H), friction angle (ɸ), the ratio of the diameter of the helical blade to the diameter of the shaft (Dp/Ds), number of helices (n), and inter-helix spacing ratio (S/Dp), on the uplift capacity of the helical pile (Qu). The helical pile was modeled and validated with the experimental results obtained from past investigations. The numerical data was then processed through an artificial neural network to develop a prediction model between the uplift capacity and varied parameters. An increment in Qu was observed with the increases in ϕ, n, H, and S/Dp. However, a decrease in Qu for single and double-helical piles was noted with an increase in Dp/Ds ratio. The outcome of the artificial neural network revealed that the best prediction of Qu was given by the SIGMOID activation function. Additionally, the sensitivity analysis showed that Qu was strongly influenced by S/Dp and least influenced by Dp/Ds ratio.
Estimation of Uplift Capacity of Helical Pile Resting in Cohesionless Soil
Transp. Infrastruct. Geotech.
Angurana, Dev Inder (Autor:in) / Yadav, Jitendra Singh (Autor:in) / Khatri, Vishwas Nand Kishor (Autor:in)
Transportation Infrastructure Geotechnology ; 11 ; 833-864
01.04.2024
32 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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