Scale effect on the anisotropy characteristics of rock joint roughness

2021 ◽  
pp. qjegh2020-066
Author(s):  
Shi-Gui Du ◽  
Kai-Qian Du ◽  
Rui Yong ◽  
Jun Ye ◽  
Zhan-You Luo
Keyword(s):  
Scale Effect ◽  
Rock Joint ◽  
Rock Joints ◽  
Roughness Coefficient ◽  
Scale Dependency ◽  
Joint Roughness Coefficient ◽  
Local Anisotropy ◽  
Joint Roughness ◽  
Threshold Length

Accurate assessment of anisotropy and scale effect of rock joint roughness is essential for evaluating the mechanical behaviour of rock joints. However, in previous studies, how to quantify roughness anisotropy of rock joints remains largely unsolved, and the research about scale effect on roughness anisotropy is not conclusive. A statistical analysis on joint roughness coefficient of different sized profiles was implemented to investigate the scale-dependency of joint roughness. The scale effect on the roughness anisotropy were investigated based on class ratio transform approach. The roughness anisotropy was characterized by local anisotropy and global anisotropy. The global anisotropy tends to be almost constant when the sample size exceeds the stationarity threshold length of 70 cm. The result shows that the global anisotropy is scale-dependent. However, the scale effect on local anisotropy is less apparent. The case study indicates that the class ratio transform approach implies its superiority in roughness anisotropy investigation.

scholarly journals A New Method for Determination of Joint Roughness Coefficient of Rock Joints

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Shigui Du ◽  
Huicai Gao ◽  
Yunjin Hu ◽  
Man Huang ◽  
Hua Zhao
Keyword(s):  
Scale Effect ◽  
Fractal Model ◽  
Rock Joints ◽  
Effective Length ◽  
Roughness Coefficient ◽  
Joint Roughness Coefficient ◽  
Joint Roughness ◽  
Exposed Rock ◽  
Study Results

The joint roughness coefficient (JRC) of rock joints has the characteristic of scale effect. JRC measured on small-size exposed rock joints should be evaluated by JRC scale effect in order to obtain the JRC of actual-scale rock joints, since field rock joints are hardly fully exposed or well saved. Based on the validity analysis of JRC scale effect, concepts of rate of JRC scale effect and effective length of JRC scale effect were proposed. Then, a graphic method for determination of the effective length of JRC scale effect was established. Study results show that the JRC of actual-scale rock joints can be obtained through a fractal model of JRC scale effect according to the statistically measured results of the JRC of small-size partial exposed rock joints and by the selection of fractal dimension of JRC scale effect and the determination of effective length of JRC scale effect.

scholarly journals Correlation between the Joint Roughness Coefficient and Rock Joint Statistical Parameters at Different Sampling Intervals

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Man Huang ◽  
Cia-chu Xia ◽  
Peng Sha ◽  
Cheng-rong Ma ◽  
Shi-gui Du
Keyword(s):  
General Formula ◽  
Rock Joint ◽  
Statistical Parameter ◽  
Rock Joints ◽  
Estimation Accuracy ◽  
Roughness Coefficient ◽  
Joint Roughness Coefficient ◽  
Joint Roughness ◽  
The Relationship ◽  
Fitting Parameters

Joint roughness coefficient (JRC) is a major factor that affects the mechanical properties of rock joints. Statistical methods that are used to calculate the JRC increasingly depend on a sampling interval (Δx). The variation rules of fitting parameters a, b, and b/a at different Δx values were analyzed on the basis of the relationship between the JRC and statistical parameter Z2. The relationship between the fitting parameters a and b was deduced in accordance with the ten standard profiles proposed by Barton. Empirical formulas for the JRC, Z2, and Δx were also established. The estimation accuracy of the JRC was the highest in the analysis of Δx values within 0.1–5.0 mm. JRC tests were conducted through inverse value comparative analysis. Results showed that the outcome calculated using the general formula and the JRC inverse values demonstrate improved agreement and verify the rationality of the general formula. The proposed formula can perform rapid and simple JRC calculation within the Δx range of 0.1–5.0 mm using Z2, thereby indicating favorable application prospects.

scholarly journals Neutrosophic Functions of the Joint Roughness Coefficient and the Shear Strength: A Case Study from the Pyroclastic Rock Mass in Shaoxing City, China

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jun Ye ◽  
Rui Yong ◽  
Qi-Feng Liang ◽  
Man Huang ◽  
Shi-Gui Du
Keyword(s):  
Shear Strength ◽  
Rock Mass ◽  
Rock Joint ◽  
Sampling Bias ◽  
Rock Joints ◽  
Joint Surface ◽  
Pyroclastic Rock ◽  
Roughness Coefficient ◽  
Joint Roughness Coefficient ◽  
Joint Roughness

Many studies have been carried out to investigate the scale effect on the shear behavior of rock joints. However, existing methods are difficult to determinate the joint roughness coefficient (JRC) and the shear strength of rock joints with incomplete and indeterminate information; the nature of scale dependency of rock joints is still unknown and remains an ongoing debate. Thus, this paper establishes two neutrosophic functions of the JRC values and the shear strength based on neutrosophic theory to express and handle the incomplete and indeterminate problems in the analyses of the JRC and the shear strength. An example, including four rock joint samples derived from the pyroclastic rock mass in Shaoxing city, China, is provided to show the effectiveness and rationality of the developed method. The experimental results demonstrate that the proposed neutrosophic functions can express and deal with the incomplete and indeterminate problems of the test data caused by geometry complexity of the rock joint surface and sampling bias. They provide a new approach for estimating the JRC values of the different-sized test profiles and the peak shear strength of rock joints.

scholarly journals Neutrosophic Function with NNs for Analyzing and Expressing Anisotropy Characteristic and Scale Effect of Joint Surface Roughness

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Yong ◽  
Leiyu Gu ◽  
Jun Ye ◽  
Shi-Gui Du ◽  
Man Huang ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Scale Effect ◽  
Large Scale ◽  
Rock Joint ◽  
Rock Joints ◽  
Joint Surface ◽  
Roughness Coefficient ◽  
Statistical Assessment ◽  
Natural Rock

The shear behavior of rock mass significantly depends upon the surface roughness of rock joints which is generally characterized by the anisotropy characteristic and the scale effect. The large-scale natural rock joint surfaces, at Qingshi Town, southeast of Changshan County, Zhejiang Province, China, were used as a case study to analyze the roughness characteristics. A statistical assessment of joint roughness coefficient (JRC) indicated the roughness anisotropy of different sized rock joints. The lower limit (JRCmean-σ) was regarded as the determinate information, and the difference between lower and upper limits represented indeterminate information. The neutrosophic number (NN) was calculated to express the various JRC values. The parametric equations for JRC anisotropic ellipse were presented based on the JRC statistical assessment of joint profiles of various orientations. The JRC values of different sized joint samples were then quantitatively described by the neutrosophic function. Finally, a neutrosophic parameter ψ for evaluating the scale effect on the surface roughness anisotropy was introduced using the ratio of maximum directional roughness to minimum directional roughness. The case study indicates that the proposed method has the superiority in moving forward from subjective assessment to quantitative and objective analysis on anisotropy characteristic and scale effect of joint surface roughness.

scholarly journals A New Method to Estimate the Joint Roughness Coefficient by Back Calculation of Shear Strength

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Jiu-yang Huan ◽  
Ming-ming He ◽  
Zhi-qiang Zhang ◽  
Ning Li
Keyword(s):  
Shear Strength ◽  
Joint Model ◽  
Rock Joints ◽  
New Method ◽  
Roughness Coefficient ◽  
Shear Direction ◽  
Joint Roughness Coefficient ◽  
Joint Roughness ◽  
Back Calculation ◽  
Smooth Joint Model

The joint roughness coefficient (JRC) is an important factor affecting the shear properties of rock joints, and its accurate estimation is a challenging task in rock engineering. Existing JRC evaluation approaches such as the empirical comparison method and the statistical parameter method have some unresolved defects. In this study, a new method is proposed for JRC estimation to overcome the deficiencies of existing approaches based on back calculation of shear strength. First, the 10 standard roughness joints are established in numerical rock samples generated by the bonded particle method (BPM). Secondly, the microscopic parameters of the intact rock and joints are calibrated, and a series of direct shear tests of joint samples are carried out under different normal stresses. Finally, the empirical relationships between shear strength and JRC are proposed under high correlation conditions. The results show that the modified smooth joint model (MSJM) is proved to better simulate the mechanical properties of rough joints than the smooth joint model (SJM). When the shear strength of target joint is substituted in the corresponding relationship, the JRC of joint along the shear direction can be conveniently obtained. In addition, the JRC values of 10 standard roughness joint profiles under shear direction of from right to left (FRTL) are obtained. By estimating the JRC of 9 target joints in the literature, it can be seen that the new method proposed in this paper can well reflect the directionality of roughness and it is convenient to apply.

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