2021
DOI: 10.1155/2021/8872873
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Suggested New Statistical Parameter for Estimating Joint Roughness Coefficient considering the Shear Direction

Abstract: The 10 standard roughness joint profiles provided a visual comparison to get the joint roughness coefficient (JRC) of rock joint surface, but the accuracy of this method is influenced by human factors. Therefore, many researchers try to evaluate the roughness morphology of joint surface through the statistical parameter method. However, JRC obtained from most of the existing statistical parameters did not reflect the directional property of joint surface. Considering the 10 standard profiles as models of diffe… Show more

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Cited by 3 publications
(3 citation statements)
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“…Obviously, this procedure ignored the effect of the protrusion size on overall roughness. The distribution law of the external force borne by the joint protrusion was rarely mentioned in the existing literature, and there was no quantitative result for reference [34][35][36]. Moreover, the size of joint protrusion in rough joints is difficult to be clearly simulated, which leads to poor correlation of corresponding analysis results [37].…”
Section: Introductionmentioning
confidence: 99%
“…Obviously, this procedure ignored the effect of the protrusion size on overall roughness. The distribution law of the external force borne by the joint protrusion was rarely mentioned in the existing literature, and there was no quantitative result for reference [34][35][36]. Moreover, the size of joint protrusion in rough joints is difficult to be clearly simulated, which leads to poor correlation of corresponding analysis results [37].…”
Section: Introductionmentioning
confidence: 99%
“…Formula Ref. JRC = 411(R P − 1) JRC = 65.9(R P − 1) 0.302 − 9.65 [21] [22] [23] [25] [27] [28] [29] JRC = −106.67(θ p + ) −0.363 + 55.34 [30] Z…”
Section: Parametermentioning
confidence: 99%
“…(max(0, y i+1 − y i )) 2 1/2 [31] JRC = −9.43(Z 2 ) −0.687 + 35.11 [30] tan θ * = − tan θ cos α [33] JRC = 14.602 ln(WPA) − 12.536 [33] With the development of scanning technology, three-dimensional (3D) statistical parameters were proposed. Based on the "local apparent inclination asperity dip", a 3D roughness parameter was proposed [32,[34][35][36].…”
Section: Parametermentioning
confidence: 99%