Investigation on the scale dependence of shear mechanical behavior of rock joints using DEM simulation

Wang, Yuan; Min, Ming

doi:10.1007/s40571-023-00577-y

Cited by 10 publications

(2 citation statements)

References 26 publications

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“…Tang, Lin [12] established a quantitative relationship between the sawtooth angle and the shear strength of the rock-mortar interfaces through the AE technique, and three AE characteristic parameters that can be used to predict interface failure were proposed. Numerical simulation methods, such as discrete element and finite element analyses, were also widely used in their research [13]. Ghazvinian, Taghichian [14] carried out simulations of the shear mechanical behavior of a weak interlayer between two rocks with high strength differences and proposed an equation on the relationship between the roughness coefficient parameter and surface statistical fractal parameters.…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis for Shear Behavior of Binary Interfaces under Different Bonded Conditions

Lv,

Han,

Zhang

et al. 2024

Applied Sciences

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The shear performance of the binary interface formed by mortar and rock cementation is a key factor influencing the stability and safety of basic engineering projects related to livelihood and economy since concrete has become one of the most widely used materials in engineering. Therefore, it is an urgent practical problem to further explore and clarify the shear failure mechanism of the mortar–rock binary interface. In response to the current research objective focused on fully bonded interfaces, this paper constructed binary interface models with different bonded conditions to perform direct shear experiments using numerical simulation methods, and the effect of bonded conditions on the shear behavior of the mortar–rock binary interface was analyzed. The results indicate that the bonded conditions have a significant influence on the shear mechanical behavior of the mortar–rock binary interface, which is mainly reflected in the stress-displacement curve characteristics, the shear strength, the fracture development and the stress distribution state. The research findings are of great theoretical significance for the further study of shear mechanics at the mortar–rock binary interface and of great practical significance for safe construction, resource conservation and disaster warning.

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Section: Introductionmentioning

confidence: 99%

Numerical Analysis for Shear Behavior of Binary Interfaces under Different Bonded Conditions

Lv,

Han,

Zhang

et al. 2024

Applied Sciences

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“…At the same time, there is an excellent modern-day geotechnical software, FLAC3D5.0, in which this law is taken as a basis and allows for predicting the behaviour of rock masses in different conditions [24,25]. The peak dilation angle reflects the comprehensive effect of the joint morphology on the shear strength [26,27]. Generally speaking, the peak dilation angle is defined as the instantaneous inclination of the shear path at the shear strength with respect to the mean plane [28].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Machine-Learning-Based Prediction Model for the Peak Dilation Angle of Rock Discontinuities

Xie,

Yao,

Yan

et al. 2023

Materials

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The peak dilation angle is an important mechanical feature of rock discontinuities, which is significant in assessing the mechanical behaviour of rock masses. Previous studies have shown that the efficiency and accuracy of traditional experimental methods and analytical models in determining the shear dilation angle are not completely satisfactory. Machine learning methods are popular due to their efficient prediction of outcomes for multiple influencing factors. In this paper, a novel hybrid machine learning model is proposed for predicting the peak dilation angle. The model incorporates support vector regression (SVR) techniques as the primary prediction tools, augmented with the grid search optimization algorithm to enhance prediction performance and optimize hyperparameters. The proposed model was employed on eighty-nine datasets with six input variables encompassing morphology and mechanical property parameters. Comparative analysis is conducted between the proposed model, the original SVR model, and existing analytical models. The results show that the proposed model surpasses both the original SVR model and analytical models, with a coefficient of determination (R2) of 0.917 and a mean absolute percentage error (MAPE) of 4.5%. Additionally, the study also reveals that normal stress is the most influential mechanical property parameter affecting the peak dilation angle. Consequently, the proposed model was shown to be effective in predicting the peak dilation angle of rock discontinuities.

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Attenuation Study and Early Warning of Formation-Influenced Shock Waves Based on Discrete Element Methods

Zhang,

Zhu,

et al. 2024

J Fail. Anal. and Preven.

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Investigation on the scale dependence of shear mechanical behavior of rock joints using DEM simulation

Cited by 10 publications

References 26 publications

Numerical Analysis for Shear Behavior of Binary Interfaces under Different Bonded Conditions

Numerical Analysis for Shear Behavior of Binary Interfaces under Different Bonded Conditions

Hybrid Machine-Learning-Based Prediction Model for the Peak Dilation Angle of Rock Discontinuities

Attenuation Study and Early Warning of Formation-Influenced Shock Waves Based on Discrete Element Methods

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