Estimation of Pile Bearing Capacity of Single Driven Pile in Sandy Soil Using Finite Element and Artificial Neural Network Methods

Harnedi Maizir, Reni Suryanita and Hendra Jingga
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Harnedi Maizir: Civil Engineering Department - Sekolah Tinggi Teknologi, Pekanbaru, Indonesia
Reni Suryanita: Civil Engineering Department, University of Riau, Pekanbaru, Indonesia
Hendra Jingga: Civil Engineering Department, University of Riau, Pekanbaru, Indonesia

International Journal of Applied and Physical Sciences, 2016, vol. 2, issue 2, 45-50

Abstract: The good estimation of pile bearing capacity, which is derived by total axial pile bearing capacity can be obtained through numerous methods such as empirical, analytical and field test. Thus, application of the methods has been a difficult task due to the uncertainties of various factors related to properties of soil and rock which, unlike other engineering materials, are subject to spatial uncertainty. On the other hand, performing field tests such as static and dynamic load test is time consuming and expensive, hence the use of finite element and Artificial Neural Networks (ANNs) methods is often of interest. This paper explains the finite element and ANNs methods to estimate the pile bearing capacity of sandy soil. The ANNs method is used to estimate the bearing capacity by using dynamic load test data. The outputs of finite element modelling were compared with a well-established empirical method for estimation of the ultimate axial bearing capacity of the pile. The results show that finite element and ANNs prediction on the percentage of the ultimate load are close to each other.

Keywords: Pile; Bearing Capacity; Artificial Neural Networks; Finite Element Method (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:apa:ijapss:2016:p:45-50

DOI: 10.20469/ijaps.2.50003-2.pdf

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