erdEducation Reform and Development2652-53642652-5372Bio-Byword Scientific Publishing Pty. Ltd.10.26689/erd.v7i7.11305ArticleExploration of the Multi-axis Model for Sandy Soilhttps://artdesignp.com/journal/erd/7/7/10.26689/erd.v7i7.11305YanHaixia2025772025-07-28In soil mechanics, multi-axis generalization is the key to the wide application of sandy soil models. The multi-axis model for sandy soil has important applications in geotechnical engineering (including earthquake engineering), numerical simulation, and other relevant fields. Although the traditional triaxial model has made remarkable progress in studying the basic behavior of sandy soil, it still has limitations when simulating the behavior under complex stress conditions. Multi-axis generalization can better simulate the complex stress states commonly encountered in practical engineering, thereby improving the applicability and accuracy of the model. This paper reviews the development history of the sandy soil multi-axis model, analyzes the influence of different yield criteria, hardening rules, and flow rules on the stress-strain relationship of sandy soil, introduces common experimental methods and numerical simulation techniques, and explores its application in engineering practice and future development trends.

Huang W, et al., 2023, Advances in Constitutive Modeling of Granular Materials: From Micro to Macro Perspectives (2018–2023). Reviews of Geotechnical Engineering, 11(2): 201–215.

Vardoulakis I, Sulem J, 2022, From Critical State to Non-Locality: A 50-Year Journey in Granular Soil Mechanics. Geotechnique, 72(10): 879–895.

Li X, Dafalias Y, 2021, A Hypoplastic Model for Sand with Enhanced Prediction of Liquefaction-Induced Shear Banding. Journal of Geotechnical and Geoenvironmental Engineering, 147(6): 04021034.

Wang Y, Sun D, 2020, A Multi-Surface Plasticity Model for Anisotropic Sand Considering Fabric Evolution. Canadian Geotechnical Journal, 57(8): 1234–1248.

Bolton M, 2022, Revisiting the Cam-Clay Model for Granular Materials: A Critical State Perspective. Geotechnique Letters, 12(3): 156–163.

Matsuoka N, Nakai T, Yamada Y, 2021, Anisotropic Constitutive Modeling of Sand Based on Micromechanical Considerations. Soils and Foundations, 61(4): 102–115.

Shahin M, Coop M, 2023, A Dilatancy Model for Sand Under Cyclic Loading Considering Fabric-Dependent Behavior. Engineering Geology, 308: 106832.

Zhang L, et al., 2020, Numerical Simulation of Tunneling-Induced Ground Deformation Using an Advanced Elastoplastic Sand Model. Tunnelling and Underground Space Technology, 98: 103345.

Cui Y, O’Sullivan C, 2021, Coupled CFD-DEM Modeling of Granular Flow Using a Non-Local Hypoplasticity Model. Computers and Geotechnics, 135: 104191.

Lu N, et al., 2023, Machine Learning-Based Constitutive Modeling of Granular Materials: A Data-Driven Framework. Computers and Geotechnics, 158: 105312.

Chen Z, Zhao J, 2022, Deep Learning for Predicting Shear Strength of Sand Under Complex Stress Paths. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 16(3): 789–805.

Alonso E, et al., 2021, Experimental Study on the Liquefaction Resistance of Sand Under Biaxial Shear Conditions. Journal of Geotechnical Engineering, 147(8): 04021029.

Indraratna B, et al., 2020, Shear Strength and Dilatancy of Railway Ballast Sands: Experimental and Modelling Insights. Geotechnical Testing Journal, 43(5): 1234–1245.