Physical Modeling of Shear Behavior of Infilled Rock Joints Under CNL and CNS Boundary Conditions

Shrivastava, Amit Kumar; Rao, K. Seshagiri

doi:10.1007/s00603-017-1318-8

Cited by 51 publications

(16 citation statements)

References 27 publications

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“…Rock joints are mechanical discontinuities developed due to varied geological processes [1]. These discontinuities are present in the form of joints, faults, bedding planes, foliations, or other recurrent planar fractures in the rock mass [2][3][4][5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study on Shear Behavior and Failure Mechanism of Bolted Heterogeneous Rock Joints under Different Anchorage Conditions

et al. 2021

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Despite their frequent natural occurrence and engineering encounter, heterogeneous rock joints (rock joints with different lithological characters on both sides of the joint surface) have been studied much less systematically. To study the shear behavior and failure mechanism of bolted heterogeneous rock joints, laboratory tests were performed on the heterogeneous rock joints having different joint roughness coefficients (JRC) under different anchorage conditions. The results indicate that shear strength increases with the increase of JRC, showing exponential growth. Under the same roughness, the shear strengths of rock joints from large to small are fully grouted, end anchorage, and without anchorage. The mechanical characteristics of the bolt and joint are poorly matched under the end anchorage condition, which is easy to cause these two to be broken one by one. Under fully grouted, the extrusion force caused by the rock bolt will diffuse around the anchorage agent and will not cause partial continuous damage. The surface damage of heterogeneous rock joints increases with the increase of JRC and presents obvious heterogeneous characteristics. The shear dislocation between the blocks under shear load results in the interaction between the bolt and surrounding media. Under the action of shear force, the bolt body produced both axial and transverse deformation, which leads to breakage of anchorage agent and rock mass. Rock bolt has a significant impact on the shear behavior of the anchorage system, and the damage of the rock bolt to rock mass should be considered in rock engineering reinforcement design.

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Section: Introductionmentioning

confidence: 99%

Experimental Study on Shear Behavior and Failure Mechanism of Bolted Heterogeneous Rock Joints under Different Anchorage Conditions

et al. 2021

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“…Xia et al (2018) carried out an empirical study on shear behaviour. Finally, much work is reported on the development of shear strength models to which Bahaaddini (2016), Casagrande et al (2018), Johansson and Stille (2014), Kumar and Verma (2016), Shrivastava and Seshagiri Rao (2018), and Zhu et al (2019) serve as examples. In summary, these numerous examples illustrate the extent of research performed on joint shearing.…”

Section: Introductionmentioning

confidence: 99%

An Approach to Compensate for the Influence of the System Normal Stiffness in CNS Direct Shear Tests

Larsson

Flansbjer

2020

Rock Mech Rock Eng

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Applying accurate normal load to a specimen in direct shear tests under constant normal stiffness (CNS) is of importance for the quality of the resulting data, which in turn influences the conclusions. However, deficiencies in the test system give rise to a normal stiffness, here designated as system normal stiffness, which results in deviations between the intended and actual applied normal loads. Aiming to reduce these deviations, this paper presents the effective normal stiffness approach applicable to closed-loop control systems. Validation through direct shear tests indicates a clear influence of the system normal stiffness on the applied normal load (13% for the test system used in this work). The ability of the approach to compensate for this influence is confirmed herein. Moreover, it is demonstrated that the differences between the measured and the nominal normal displacements are established by the normal load increment divided by the system normal stiffness. This further demonstrates the existence of the system normal stiffness. To employ the effective normal stiffness approach, the intended normal stiffness (user defined) and the system normal stiffness must be known. The latter is determined from a calibration curve based on normal loading tests using a stiff test dummy. Finally, a procedure is presented to estimate errors originating from the application of an approximate representation of the system normal stiffness. The approach is shown to effectively reduce the deviations between intended normal loads and the actual applied normal loads.

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“…These simplified models having been validated by direct shear tests performed under constant normal load conditions (CNL), for certain load conditions. However, parameters such as the presence of infill material and also normal stiffness caused by the surrounding rock mass or rock bolts, which significantly influence the shear strength of the discontinuities are not considered (Ladanyi & Archambault, 1977;Papaliangas et al, 1993;Haque, 1999;Haque & Indraratna, 2000;Indraratna et al, 1999Indraratna et al, , 2005Indraratna et al, , 2010Indraratna et al, , 2012Indraratna et al, , 2013Indraratna et al, , 2014Indraratna et al, , 2015Oliveira et al, 2009;Naghadehi, 2015;Karakus et al, 2016;Mehrishal et al, 2016;Shrivastava & Rao, 2017). On the other hand, the use of analytical models for rationally considering the effect of the infill and the normal stiffness of the rock discontinuities is hampered by the number of parameters required.…”

Section: Introductionmentioning

confidence: 99%

A predictive model for the peak shear strength of infilled soft rock joints developed with a multilayer perceptron

Leite¹,

Neto²

2020

S&R

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Several analytical methodologies help estimate the shear strength of rock discontinuities whose main limitations are the difficulty to obtain all necessary parameters to satisfactorily represent the boundary conditions and influence of infill materials. The objective of this study is to present a predictive model of peak shear strength for soft rock discontinuities developed making use of an artificial neural network known as multilayer perceptron. The model's input variables are: normal stiffness; initial normal stress acting on the discontinuity; joint roughness coefficient (JRC); ratio t/a (fill thickness/asperity height); uniaxial compressive strength and the basic friction angle of the intact rock; and finally the internal friction angle of infill material. To do so, results from 115 direct shear tests, with different soft rock discontinuities conditions were used. The herein proposed ANN predictive model, with an architecture 7-20-1, have shown coefficient of correlation in training and validation of 99.8 % and 99 %, respectively. The results from the model satisfactorily fit the experimental data and were also able to represent the influence of the input variables on the peak shear strength of soft rock discontinuities for different infill and boundary conditions.

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Physical Modeling of Shear Behavior of Infilled Rock Joints Under CNL and CNS Boundary Conditions

Cited by 51 publications

References 27 publications

Experimental Study on Shear Behavior and Failure Mechanism of Bolted Heterogeneous Rock Joints under Different Anchorage Conditions

Experimental Study on Shear Behavior and Failure Mechanism of Bolted Heterogeneous Rock Joints under Different Anchorage Conditions

An Approach to Compensate for the Influence of the System Normal Stiffness in CNS Direct Shear Tests

A predictive model for the peak shear strength of infilled soft rock joints developed with a multilayer perceptron

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