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openalexFrontiers in Built Environment2026-07-24Cited by 0

Calculation of effective constitutive stiffness matrices for a geocell layer and analysis of reinforcement mechanisms in geocell-reinforced embankments

Changjun Yin, Ahmed Adam Khalifa Gowi, Yi Luo, Mingzhe Zhai, Junjia Shi, Zhiyong Sun

In this study, by incorporating the transverse shear stiffness matrix <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m29"> <mml:mrow> <mml:mi mathvariant="bold">E</mml:mi> </mml:mrow> </mml:math> derived from unit-cell analysis, the geocell layer in geocell-reinforced soil structures was, for the first time, integrated as an equivalent anisotropic thick plate into a full-scale macrostructural geotechnical model. Based on this framework, a comprehensive homogenized numerical simulation (HNS) was developed to evaluate the system’s mechanical behavior and reinforcement mechanisms. The main research contents and conclusions are as follows: (1) the constitutive stiffness matrices <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m30"> <mml:mrow> <mml:mi mathvariant="bold">A</mml:mi> <mml:mi mathvariant="bold">B</mml:mi> <mml:mi mathvariant="bold">D</mml:mi> <mml:mi mathvariant="bold">E</mml:mi> </mml:mrow> </mml:math> of the equivalent thick plate for the geocell layer were calculated using the plate-shell asymptotic homogenization method and a self-developed program; (2) the reliability and efficiency of using HNSs for analyzing the mechanical behavior of geocell-reinforced embankments were validated by comparing the numerical results with independent benchmarks; and (3) the mechanical mechanisms of the lateral resistance effect, vertical stress diffusion effect, and membrane effect were systematically analyzed. The results demonstrate that the proposed HNS framework successfully reproduced vertical settlement profiles, closely matching the experimental data within an acceptable engineering error. Furthermore, compared with direct numerical simulations, the HNS approach achieved an exceptional reduction in computational time, making large-scale parametric optimization practically efficient.

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