Bayesian optimization for CPT-based prediction of impact pile drivability

Buckley, Róisín and Chen, Yuling Max and Sheil, Brian and Suryasentana, Stephen and Xu, Diarmid and Doherty, James and Randolph, Mark (2023) Bayesian optimization for CPT-based prediction of impact pile drivability. Journal of Geotechnical and Geoenvironmental Engineering, 149 (11). 04023100. ISSN 1090-0241 (https://doi.org/10.1061/JGGEFK.GTENG-11385)

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Abstract

Pile drivability predictions require information on the pile geometry, impact hammer, and the soil resistance to driving (SRD). Current SRD prediction methods are based on databases of long slender piles from the oil and gas industry and new, robust, and adaptable methods are required to predict SRD for current offshore pile geometries. This paper describes an optimization framework to update uncertain model parameters in existing axial static design methods to calibrate SRD. The approach is demonstrated using a case study from a German offshore wind site. The optimization process is undertaken using a robust Bayesian approach to dynamically update uncertain variables during driving to improve simulations. The existing method is shown to perform well for piles with geometries that reflect the underlying database such that only minimal optimization is required. For larger diameter piles, relative to the prior best estimate, optimized results are shown to provide significant improvements in the mean calculations and associated variance of pile drivability as more data is acquired. The optimized parameters can be used to predict SRD for similar piles in analogous ground conditions. The demonstrated framework is adaptable and can be used to develop site-specific calibrations and advance new SRD methods where large pile driving data sets are available.

ORCID iDs

Buckley, Róisín, Chen, Yuling Max, Sheil, Brian, Suryasentana, Stephen ORCID logoORCID: https://orcid.org/0000-0001-5460-5089, Xu, Diarmid, Doherty, James and Randolph, Mark;
  • Item type:Article
    ID code:86816
    Dates:
    Date
    Event
    1 November 2023
    Published
    31 August 2023
    Published Online
    26 June 2023
    Accepted
    Notes:Copyright © 2023 American Society of Civil Engineers. This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://doi.org/10.1061/JGGEFK.GTENG-1138.
    Subjects:Technology > Engineering (General). Civil engineering (General)
    Department:Faculty of Engineering > Civil and Environmental Engineering
    Depositing user: Pure Administrator
    Date deposited:02 Oct 2023 07:37
    Last modified:19 Nov 2024 01:18
    URI:https://strathprints.strath.ac.uk/id/eprint/86816
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