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    Artificial intelligence for modelling load-settlement response of axially loaded bored piles

    Access Status
    Fulltext not available
    Authors
    Shahin, Mohamed
    Date
    2014
    Type
    Conference Paper
    
    Metadata
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    Citation
    Shahin, M. 2014. Artificial intelligence for modelling load-settlement response of axially loaded bored piles, in Hicks, M. and Brinkgreve, R. and Rohe, A. (ed), 8th European Conference on Numerical Methods in Geotechnical Engineering, Jun 18-20 2014, pp. 491-495. Delft, Netherlands: CRC Press, Taylor and Francis Group.
    Source Title
    Numerical Methods in Geotechnical Engineering
    Source Conference
    8th European Conference on Numerical Methods in Geotechnical Engineering
    DOI
    10.1201/b17017-88
    ISBN
    978-1-138-00146-6
    URI
    http://hdl.handle.net/20.500.11937/31255
    Collection
    • Curtin Research Publications
    Abstract

    The design of pile foundations requires reliable estimation of the pile load-carrying capacity and settlement. Design for bearing capacity and design for settlement are traditionally carried out separately. However, soil resistance and settlement are influenced by each other and the design of pile foundations should thus consider the bearing capacity and settlement inseparably. This requires the full load-settlement response of piles to be well predicted. However, it is well known that the actual load-settlement behavior of pile foundations can only be obtained by full-scale static load tests carried out in-situ, which are expensive and time-consuming. In this paper, artificial intelligence (AI) using the recurrent neural networks (RNNs) is used to develop a prediction model that can resemble the full load-settlement response of bored piles subjected to axial loading. The developed RNN model is calibrated and validated using several in-situ full-scale pile load tests, as well as cone penetration test (CPT) data. The results indicate that the RNN model has the ability to reliably predict the load-settlement behavior of axially loaded bored piles and can thus be used by geotechnical engineers for routine design practice.

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