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<p>This paper investigates the bearing capacity of perforated mudmat foundations on anisotropic clays using 3D finite element limit analysis (FELA). Despite the growing application of perforated foundations in offshore engineering, their effects on load transfer mechanisms and bearing capacity in anisotropic soils remain insufficiently investigated. Three key dimensionless parameters are examined: the perforation ratio (<i>R</i>), the foundation aspect ratio (<i>B/L</i>), and the anisotropic shear strength ratio (<i>r</i><sub><i>e</i></sub>). The results indicate that the perforated ratio slightly affects the bearing capacity, the available area of the bearing foundation decreased by the perforations. An increase in <i>R</i> with a low <i>B/L</i> ratio leads to a rise in&#xa0;<i>N</i><sub><i>c</i></sub>. On the other hand, a higher <i>B/L</i> reduces the bearing capacity factor (<i>N</i><sub><i>c</i></sub>). Furthermore, the anisotropic shear strength ratio (<i>r</i><sub><i>e</i></sub>) has a significant impact on <i>N</i><sub><i>c</i></sub>. In addition, the study introduces machine learning approaches to solve the complex relationship between the input parameters and the output parameter without the difficult calculation. Design equations for bearing capacity prediction are developed using genetic programming, achieving high <i>R</i><sup><i>2</i></sup> value of 0.99022 and 0.98828 for training and testing sets, respectively. The findings provide valuable insights for optimizing the design of offshore foundations on anisotropic clay.</p>

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Bearing Capacity Prediction of Perforated Mudmat Foundations on Anisotropic Clays Based on FELA and Genetic Programming

  • 期刊论文

  • 发表日期：

    2025年8月14日

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  • Rungroad Suppakul,
  • Wittaya Jitchaijaroen,
  • Rithy Domphoeun,
  • Peem Nuaklong,
  • Suraparb Keawsawasvong,
  • Pitthaya Jamsawang

摘要

This paper investigates the bearing capacity of perforated mudmat foundations on anisotropic clays using 3D finite element limit analysis (FELA). Despite the growing application of perforated foundations in offshore engineering, their effects on load transfer mechanisms and bearing capacity in anisotropic soils remain insufficiently investigated. Three key dimensionless parameters are examined: the perforation ratio (R), the foundation aspect ratio (B/L), and the anisotropic shear strength ratio (re). The results indicate that the perforated ratio slightly affects the bearing capacity, the available area of the bearing foundation decreased by the perforations. An increase in R with a low B/L ratio leads to a rise in Nc. On the other hand, a higher B/L reduces the bearing capacity factor (Nc). Furthermore, the anisotropic shear strength ratio (re) has a significant impact on Nc. In addition, the study introduces machine learning approaches to solve the complex relationship between the input parameters and the output parameter without the difficult calculation. Design equations for bearing capacity prediction are developed using genetic programming, achieving high R2 value of 0.99022 and 0.98828 for training and testing sets, respectively. The findings provide valuable insights for optimizing the design of offshore foundations on anisotropic clay.