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May 27, 2026Journal of Marine Science and Engineering0 citationsOpen Access

Numerical Investigation of Poisson’s Ratio Effects on Ice–Structure Interaction Using the Peridynamic Method

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YZY L ZhangLYLiyu YeCWC Z Wang

Key Points

  • The study aims to analyze how different Poisson's ratios influence ice failure mechanisms and ice-induced loads using the peridynamic method.
  • Employs the peridynamic method with discrete energy release rate criterion in two scenarios: cylindrical impact and ice-structure interaction.
  • Computes and compares Poisson's ratios through benchmark compression tests for various prescribed values.
  • Demonstrates the limitations of the bond-based model in accurately modeling ice mechanics.
  • Computed Poisson’s ratios of 0.215, 0.258, 0.333, and 0.401 corresponded to relative errors of 7.5%, 3.2%, 1.02%, and 0.38%, respectively.
  • Fracture simulations showed variation in Poisson’s ratio affects ice fracture patterns and load distributions.
  • Findings emphasize the need for state-based PD formulations for improved modeling of ice-induced mechanical responses.

Abstract

The peridynamic (PD) method has been widely utilized in the numerical modelling of ice–structure interactions due to its capability to naturally capture material failure and fracture evolution. PD formulations can be categorized into bond-based and state-based models. While the bond-based model offers computational simplicity, it inherently restricts Poisson’s ratio to 1/4 in three-dimensional (3D) simulations and 1/3 in two-dimensional (2D) simulations. In contrast, the state-based model allows for arbitrary Poisson’s ratios, which is essential for accurately modelling ice mechanics, as Poisson’s ratio of ice commonly exceeds 0.33 and can reach up to 0.42. This study employs the PD method coupled with the discrete energy release rate criterion to analyze the influence of Poisson’s ratio on ice failure mechanisms and ice-induced loads in two typical scenarios: cylindrical impact on an ice disc and ice–structure interaction with a propeller blade. The benchmark compression test yielded computed Poisson’s ratios of 0.215, 0.258, 0.333, and 0.401 for prescribed values of 0.2, 0.25, 0.33, and 0.40, corresponding to relative errors of 7.5%, 3.2%, 1.02%, and 0.38%, respectively. And the fracture simulations indicate that variations in Poisson’s ratio affects ice fracture patterns and load distributions, underscoring the limitations of the bond-based PD model in accurately representing ice–structure interactions. These findings highlight the necessity of adopting state-based PD formulations for improved numerical predictions of ice-induced mechanical responses.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a168a7f0c924ddd1bd592dfhttps://doi.org/10.3390/jmse14100886
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