Volumetric calculation method and temperature characteristics of frozen soil in mechanical testing

Zhang, Shujuan; Sun, Ziyong; Xu, Xin; Du, Haimin

doi:10.1016/j.coldregions.2012.09.008

Cited by 14 publications

(5 citation statements)

References 4 publications

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“…Especially, when other methods of soil improvement are considered infeasible, AGF could be the only way if it is analysed and designed properly. Furthermore, AGF is an environmentally friendly method that has no lasting negative effects on soil and groundwater considering its reversibility [2][3][4][5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of the Mechanical Behavior of Frozen Soils - A Case Study of Tabriz Subway

Esmaeili‐Falak

Katebi

2017

Period. Polytech. Civil Eng.

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The mechanical properties of frozen ground are key parameters in design and implementation of artificial ground freezing (AGF) in underground projects. Soil samples were obtained from the urban underground railway project site in Tabriz, Iran. The specimens were classified as SP and CL according to the USCS. The specimens were remolded in accordance with the site conditions. Over 120 triaxial compression tests were conducted on the frozen samples at different temperatures, confining pressures and strain rates. The results show that the frozen SP and CL soils exhibit strain-softening and strain-hardening behaviour, respectively. In all cases, Young's modulus increases with decreasing temperature and increasing strain rate and confining pressure. Also, the shear strength increases with decreasing temperature and increasing strain rate. In all tests, the Young's modulus and shear strength of the SP soil are greater than the CL soil. Based on the results of this research, the application of artificial ground freezing was recommended for coarse-grained and non-cohesive soils like SP in the Tabriz underground railway project.

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Section: Introductionmentioning

confidence: 99%

Experimental Study of the Mechanical Behavior of Frozen Soils - A Case Study of Tabriz Subway

Esmaeili‐Falak

Katebi

2017

Period. Polytech. Civil Eng.

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“…Because of its direct influence on the amount of unfrozen water and on the strength of intergranular ice in a frozen soil, temperature has a marked effect on all aspects of its mechanical behavior. Many documents show that some mechanical parameters of frozen soil can be approximated by the formulae (Andersland and Landanyi, 2004;Lai et al, 2009;Li et al, 2009;Wu and Ma, 1994;Zhang et al, 2013).…”

Section: Experimental and Numerical Modelmentioning

confidence: 99%

Experimental and numerical investigations on frost damage mechanism of a canal in cold regions

Zhang

Tian³

et al. 2015

Cold Regions Science and Technology

100

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“…To precisely evaluate the peak shear strength of marine soft clay sediment, researchers have designed specialized testing equipment capable of simulating the unique service conditions within these environments [30][31][32][33]. Notably, Chao and Fowmes [33] introduced a custom apparatus capable of quantifying the peak shear strength of soil or the soil-geosynthetics interface under varying temperature conditions during drying-wetting cycles.…”

Section: Introductionmentioning

confidence: 99%

Estimating Shear Strength of Marine Soft Clay Sediment: Experimental Research and Hybrid Ensemble Artificial Intelligence Modeling

Hu,

Li,

Wang

et al. 2024

Water

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In the design of offshore engineering foundations, a critical consideration involves determining the peak shear strength of marine soft clay sediment. To enhance the accuracy of estimating this value, a database containing 729 direct shear tests on marine soft clay sediment was established. Employing a machine learning approach, the Particle Swarm Optimization algorithm (PSO) was integrated with the Adaptive Boosting Algorithm (ADA) and Back Propagation Artificial Neural Network (BPANN). This novel methodology represents the initial effort to employ such a model for predicting the peak shear strength of the soil. To validate the proposed approach, four conventional machine learning algorithms were also developed as references, including PSO-optimized BPANN, Support Vector Machine (SVM), BPANN, and ADA-BPANN. The study results show that the PSO-BPANN model, which has undergone optimization via Particle Swarm Optimization (PSO), has prediction accuracy and efficiency in determining the peak shear performance of marine soft clay sediments that surpass that offered by traditional machine learning models. Additionally, a sensitivity analysis conducted with this innovative model highlights the notable impact of factors such as normal stress, initial soil density, the number of drying–wetting cycles, and average soil particle size on the peak shear strength of this type of sediment, while the impact of initial soil moisture content and temperature is comparatively minor. Finally, an analytical formula derived from the novel algorithm allows for precise estimation of the peak shear strength of marine soft clay sediment, catering to individuals lacking a background in machine learning.

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Volumetric calculation method and temperature characteristics of frozen soil in mechanical testing

Cited by 14 publications

References 4 publications

Experimental Study of the Mechanical Behavior of Frozen Soils - A Case Study of Tabriz Subway

Experimental Study of the Mechanical Behavior of Frozen Soils - A Case Study of Tabriz Subway

Experimental and numerical investigations on frost damage mechanism of a canal in cold regions

Estimating Shear Strength of Marine Soft Clay Sediment: Experimental Research and Hybrid Ensemble Artificial Intelligence Modeling

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