Anisotropy of Rock Profile JRC Values and Its Empirical Formula: A Case Study on Yellow Rust Granite

Wang, Min; Cao, Ping; Chen, Yu

doi:10.1007/s10706-017-0199-7

Cited by 16 publications

(7 citation statements)

References 34 publications

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“…Failure of Joints e contact between the upper and lower surfaces of rock joint is closely related to normal stress and joint morphology, whereby a greater normal stress indicates a tighter contact [27][28][29][30][31]. Under shearing, two failure mechanisms occur through contact.…”

Section: Nonlinear Shear Behavior and Progressivementioning

confidence: 99%

Shear Resistance of Rock Joint under Nonuniform Normal Stress

Lin

Chen

et al. 2020

Advances in Materials Science and Engineering

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Many factors influence the shear resistance of rock joints. Among them, the above overburden load is the most important factor. The uneven thickness of the overburden causes the joints to be subjected to the nonuniform distribution load. While the peak shear strength shows nonlinear relationship with normal stress, linear superposition cannot be used to calculate the overall shear resistance of joint under nonuniform normal stress distribution. In this paper, the nonlinear shear strength model, JRC-JCS model, is applied to study the overall shear resistance of the joint under four nonuniform distribution patterns of normal stress. The results show that when the normal stress is distributed in a nonuniform way, the shear resistance provided by rock joint as a whole decreases with the increase of the normal stress distribution interval. Given the nonuniform distribution of normal stress along the joint, the shear resistance obtained by the Mohr-Coulomb linear model is overestimated. In order to give full play to the overall shear performance of the joint, the shear strength at different positions on the joint should be as close as possible. Then, the shear strength of joint parts can enter peak state condition simultaneously, at which time the shear strength is fully exerted.

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Section: Nonlinear Shear Behavior and Progressivementioning

confidence: 99%

Shear Resistance of Rock Joint under Nonuniform Normal Stress

Lin

Chen

et al. 2020

Advances in Materials Science and Engineering

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“…Also, the uniform distribution can be followed. Moreover, embedded Fish language by servo control method is used to control the model of the "wall" movement to realize the uniaxial and conventional triaxial and the numerical simulation of the direct shear test [13,[29][30][31][32][33]. A parallel bond model is used for particle bonding and the parallel bonding radius is set to 1.0.…”

Section: Modelingmentioning

confidence: 99%

Relationship of rock microscopic parameters with the elastic modulus and strength

Cheng¹,

Yang²,

He³

2019

J. vibroeng.

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The microscopic damage of materials will induce changes in the macroscopic mechanical characteristics of rock material. When simulating engineering problems using the discrete element method, to explore the macroscopic mechanical response of rock material, the microscopic parameters that match the macro material characteristics must be obtained. In this paper, the influence of macroscopic mechanical properties of rock materials is studied through the variation of microscopic parameters, and the quantitative relation between macroscopic parameters of rock material is discussed. The results show that, (1) In accordance with the order of influencing factors, the parameters affecting the elastic modulus of the specimen are parallel bond elastic modulus, particle contact modulus, and parallel bond stiffness ratio. (2) The Poisson's ratio of the specimen was most influenced by the parallel bond stiffness ratio, and their relation was nonlinear. The influence of parallel bond modulus and friction factor on the Poisson's ratio was negatively correlated. (3) The effect of particle contact stiffness ratio, parallel bond stiffness ratio, and particle contact modulus on the uniaxial compressive strength was less than that of the particle friction factor.

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“…By considering the roughness of joint (JRC) and presenting 10 standard joint contour curves, Barton and Choubey [14] established the JRC-JCS shear strength model, which is popular in evaluating rock mass stability in geotechnical engineering. Despite empowering a significant efficacy in the shear strength calculation of jointed rock mass, it incurs some controversies with respect to the quantification to the joint roughness, promoting a wide pursue of the determination method of JRC in recent years [15][16][17]. For example, Tse et al [15] studied the relationship between 11 joint parameters and JRC value.…”

Section: Introductionmentioning

confidence: 99%

Determination of Joint Surface Roughness Based on 3D Statistical Morphology Characteristic

Lin

Qin

Wang

et al. 2021

Advances in Civil Engineering

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Roughness significantly affects the shear behavior of rock joints, which are widely encountered in geotechnical engineering. Since the existing calculation methods on the joint roughness coefficient (JRC) fail to obtain a sufficiently accurate value of JRC, a new determination method was proposed in this study, where the 3D laser scanning technique and self-compiled Python code, as well as the statistical parameter methods, were applied. Then, the shear strength of jointed rock was evaluated via Barton's model, and therefore, a comprehensive comparison between the calculating results and experimental results was executed. Ultimately, the influencing factors of roughness profile extraction on the accuracy of JRC value, such as the measuring point interval, profile number, and measuring direction, were investigated. The results show that (1) equipped with the 3D laser scanning technique, the roughness profiles can be accurately extracted via the self-compiled Python code, (2) an excellent consistency of shear strength could be observed between the calculating value and experimental results, verifying the validity and accuracy of the proposed method, and (3) a smaller measuring point interval can produce a more accurate digital profile and more accurate JRC value. To a certain extent, the more the sample numbers of profiles, the smaller the value of JRC.

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Anisotropy of Rock Profile JRC Values and Its Empirical Formula: A Case Study on Yellow Rust Granite

Cited by 16 publications

References 34 publications

Shear Resistance of Rock Joint under Nonuniform Normal Stress

Shear Resistance of Rock Joint under Nonuniform Normal Stress

Relationship of rock microscopic parameters with the elastic modulus and strength

Determination of Joint Surface Roughness Based on 3D Statistical Morphology Characteristic

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