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Data-driven 1D design model for monotonic lateral loading of monopile foundations

Ioannis Kamas*, Stephen K. Suryasentana, Harvey J. Burd, Byron W. Byrne

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Monopiles are a widely-used foundation system for offshore wind turbine support structures. In current practice, design calculations typically employ one-dimensional (1D) models in which the monopile is represented as an embedded beam. The current study presents a data-driven 1D design model for the analysis of offshore monopiles subjected to monotonic lateral load and moment loading. The method is based on the PISA design model framework; enhancements are incorporated in the model to improve its accuracy, scalability and to facilitate applications to a wide range of geotechnical conditions. The data-driven model incorporates a spline-based parametrisation of the soil reaction curves combined with machine learning techniques. The model is calibrated using a database of previously-published three-dimensional finite element calibration analyses. The method described in the current paper is concerned with:•Modifications to the PISA design model framework to develop a data-driven 1D design model.•Calibration of the data-driven 1D model for ground conditions comprising: (i) offshore glacial tills with varying strength-stiffness properties, and (ii) sands with a wide range of relative densities.•Validation of the proposed method by comparing 1D model predictions for monopiles in homogeneous and layered soils with detailed 3D finite element analyses.
Original languageEnglish
Article number103738
Number of pages20
JournalMethodsX
Volume16
Early online date26 Nov 2025
DOIs
Publication statusE-pub ahead of print - 26 Nov 2025

Funding

Ioannis Kamas and Stephen K. Suryasentana acknowledge the support of Ørsted in providing funding to support their research. Byron Byrne is supported by the Royal Academy of Engineering under the Research Chairs and Senior Research Fellowships scheme.

Keywords

  • machine learning
  • Pisa
  • soil-structure interaction
  • monopile design
  • offshore geotechnical engineering

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