Load-settlement modeling of axially loaded steel driven piles using CPT-based recurrent neural networks
Access Status
Authors
Date
2014Type
Metadata
Show full item recordCitation
Source Title
ISSN
Remarks
NOTICE: this is the author’s version of a work that was accepted for publication in the journal Soils and Foundations. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in the journal Soils and Foundations, Vol.54 iss.3 (2014). DOI: http://doi.org/10.1016/j.sandf.2014.04.015
Collection
Abstract
The design of pile foundations requires good estimation of the pile load-carrying capacity and settlement. Design for bearing capacity and design for settlement have been traditionally carried out separately. However, soil resistance and settlement are influenced by each other and 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 response of pile foundations can only be obtained by load tests carried out in-situ, which are expensive and time-consuming. In this technical note, the recurrent neural networks (RNNs) were used to develop a prediction model that can resemble the load-settlement response of steel driven piles subjected to axial loading. The developed RNN model was 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 developed RNN model has the ability to reliably predict the load-settlement response of axially loaded steel driven piles and can thus be used by geotechnical engineers for routine design practice.
Related items
Showing items related by title, author, creator and subject.
-
Alkroosh, Iyad Salim Jabor (2011)This thesis presents the development of numerical models which are intended to be used to predict the bearing capacity and the load-settlement behaviour of pile foundations embedded in sand and mixed soils. Two artificial ...
-
Artificial intelligence for modeling load-settlement response of axially loaded (steel) driven pilesShahin, Mohamed (2013)The design of pile foundations requires good estimation of the pile load-carrying capacity and settlement. Design for bearing capacity and design for settlement have been traditionally carried out separately. However, ...
-
Shahin, Mohamed (2014)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 ...