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<p>Helical anchors offer rapid installation and passive resistance, but inherent soil heterogeneity challenges traditional bearing capacity assessments. While incorporating spatial variability is critical, comprehensive probabilistic studies have been limited by the prohibitive computational costs of full three-dimensional (3D) simulations. To overcome this limitation, this study introduces a highly efficient axisymmetric random finite element framework to evaluate the probabilistic pullout behavior of multi-plate helical anchors. This approach is rigorously validated, demonstrating less than a 1% difference in mean uplift capacity compared to complex 3D models and a 10% mean difference against experimental centrifuge data. Utilizing this framework, 74,000 Monte Carlo simulations across 74 scenarios were conducted to evaluate the effects of embedment depth ratio (H/D), plate spacing ratio (S/D), number of plates (n), undrained shear strength variability (COVsu), and vertical correlation length (CLy) on the breakout factor. Results reveal critical design trade-offs: increasing embedment and adding plates enhances mean capacity but severely amplifies uncertainty, rendering deterministic methods unconservative in highly variable soils. Optimal group interaction occurs between S/D = 1.5 and 2.0, whereas spacing beyond S/D = 3 triggers independent plate failure. Furthermore, vertical correlation length is identified as a critical parameter; longer values amplify capacity variability up to threefold due to extended coherent soil layers. These findings underscore the necessity of reliability-based design and validate the proposed framework as a robust assessment tool.</p>

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Reliability Assessment of Helical Anchor Pullout Capacity in Cohesive Soil: An Efficient Spatial Random Field Modelling Approach

  • 期刊论文

  • 发表日期：

    2026年5月18日

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  • Niloofar Tahavvori,
  • Mohammad Aminpour,
  • Mehran Karimpour-Fard,
  • Habib Shahnazari

摘要

Helical anchors offer rapid installation and passive resistance, but inherent soil heterogeneity challenges traditional bearing capacity assessments. While incorporating spatial variability is critical, comprehensive probabilistic studies have been limited by the prohibitive computational costs of full three-dimensional (3D) simulations. To overcome this limitation, this study introduces a highly efficient axisymmetric random finite element framework to evaluate the probabilistic pullout behavior of multi-plate helical anchors. This approach is rigorously validated, demonstrating less than a 1% difference in mean uplift capacity compared to complex 3D models and a 10% mean difference against experimental centrifuge data. Utilizing this framework, 74,000 Monte Carlo simulations across 74 scenarios were conducted to evaluate the effects of embedment depth ratio (H/D), plate spacing ratio (S/D), number of plates (n), undrained shear strength variability (COVsu), and vertical correlation length (CLy) on the breakout factor. Results reveal critical design trade-offs: increasing embedment and adding plates enhances mean capacity but severely amplifies uncertainty, rendering deterministic methods unconservative in highly variable soils. Optimal group interaction occurs between S/D = 1.5 and 2.0, whereas spacing beyond S/D = 3 triggers independent plate failure. Furthermore, vertical correlation length is identified as a critical parameter; longer values amplify capacity variability up to threefold due to extended coherent soil layers. These findings underscore the necessity of reliability-based design and validate the proposed framework as a robust assessment tool.