The effects of rock joint characteristics and normal stress level on the stiffness of rock joints

Abolfazli, Milad; Fahimifar, Ahmad

doi:10.1007/s12517-020-05934-2

Cited by 6 publications

(6 citation statements)

References 27 publications

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“…e reverse JRC of the standard profiles were obtained by substituting Sa shear condition obtained under the shear condition of FRTL into (8). e results showed that the JRC of each profile varied greatly in different directions, which indicated that Sa can well reflect the directionality of roughness.…”

Section: Resultsmentioning

confidence: 99%

“…e Sa and corresponding JRC values calculated under the shear condition of FLTR and FRTL are shown in Table 7. e JRC values of joint 1,3,6,7,8,18,19,20, and 21 were corrected by (10). e results showed that the difference between the forward and reverse JRC of the joint profile was sometimes small but at other times large.…”

Section: Jrc Estimation Of the Joint Profiles Given In The Literaturementioning

confidence: 98%

“…In each shear direction, 201 joint profiles were extracted with an interval of 0.5 mm by Geomagic Studio software. e JRC of each joint profile was obtained by calculating its Sa value at 0.5 mm sampling interval and substituting it into (8). After the uniaxial compression test and direct shear test, the shear strength of joint specimens in different directions was obtained.…”

Section: Jrc Estimation Of the Natural Joint Surfacementioning

confidence: 99%

“…For unfilled rock joint, the irregular morphology of the joint surface is one important factor to control the shear strength of joints. erefore, how to describe it quickly and accurately is of crucial importance [5][6][7][8]. Barton [9] proposed the JRC-JCS model widely used in engineering through the direct shear test of 136 natural joint specimens and put forward the joint roughness coefficient (JRC) to quantitatively describe the irregular morphology of the joint for the first time.…”

Section: Introductionmentioning

confidence: 99%

“…In order to better understand the directional properties of joint roughness, the forward JRC was defined to describe the roughness obtained under the shear condition of FLTR, and the reverse JRC was defined to describe the roughness obtained under the shear condition of FRTL. Under the shear condition of FRTL, the values of Sa corresponding to standard roughness profiles were calculated by (8). e reverse JRC of each profile could be obtained by substituting the data of Sa into (8) as shown in Table 4.…”

mentioning

confidence: 99%

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Suggested New Statistical Parameter for Estimating Joint Roughness Coefficient considering the Shear Direction

Zhang

Huan

et al. 2021

Advances in Civil Engineering

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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 different roughness joints, we proposed a new idea for the accurate estimation of JRC. Based on the concept of area difference, the average of positive area difference (Sa) and sum of positive area difference (Ss) were first proposed to reflect the roughness of joint surfaces on the basis of directional property, and their fitting relationship with JRC was also investigated. The result showed that the Sa and Ss calculated by shearing from right to left (FRTL) and JRC backcalculated from right to left (FRTL) came to a satisfying power law. The correlation between JRC and Sa was better than that of Ss. The deviation between the predicted value calculated by Sa and the true value was smaller than that obtained from the existing statistical parameters. Therefore, Sa was recommended as a new statistical parameter to predict the JRC value of joint profile. As the sampling interval increased from 0.5 to 4 mm, the correlation between Sa and JRC gradually decreased, and the accuracy of the prediction results also declined. Compared with the single JRC values for joint profiles mentioned in the literature, the forward and reverse JRC were obtained. Based on the laboratory direct shear test of the natural joint surface, the JRC values of two joint surfaces in four shear directions were backcalculated by the JRC-JCS model. Based on 3D scanning and point cloud data processing technology, JRC of joint surface in different directions were obtained by Sa method, and they are very close to those obtained by JRC-JCS model. It is confirmed that Sa could accurately estimate the joint roughness coefficient and reflect its anisotropy.

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Section: Resultsmentioning

confidence: 99%