Experimental Technology for the Shear Strength of the Series-Scale Rock Joint Model

Huang, Man; Hong, Chenjie; Du, Shigui; Luo, Zhiwei

doi:10.1007/s00603-020-02241-w

Cited by 36 publications

(4 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the International Society for Rock Mechanics [ 26 ], the size and shape of the specimen for the laboratory determination of the shear strength of the rock joint are recommended to have a regular cross section, and the width of the test plane should be at least 48 mm. According to the commonly used direct shear apparatus, square-shaped specimens with side lengths of 100 or 150 mm were mainly used [ 27 , 28 ]. For the texture of the rock joint surface, textures with dull colors and repeating or symmetrical patterns may cause the resultant 3D model to be incomplete, decrease the accuracy of the model, and even lead to 3D reconstruction failure.…”

Section: Methodsmentioning

confidence: 99%

Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry

Fang

Jiang

et al. 2021

Sensors

View full text Add to dashboard Cite

The measurement of rock joint surfaces is essential for the estimation of the shear strength of the rock discontinuities in rock engineering. Commonly used techniques for the acquisition of the morphology of the surfaces, such as profilometers and laser scanners, either have low accuracy or high cost. Therefore, a high-speed, low-cost, and high-accuracy method for obtaining the topography of the joint surfaces is necessary. In this paper, a smartphone structure from motion (SfM) photogrammetric solution for measuring rock joint surfaces is presented and evaluated. Image datasets of two rock joint specimens were taken under two different modes by using an iPhone 6s, a Pixel 2, and a T329t and subsequently processed through SfM-based software to obtain 3D models. The technique for measuring rock joint surfaces was evaluated using the root mean square error (RMSE) of the cloud-to-cloud distance and the mean error of the joint roughness coefficient (JRC). The results show that the RMSEs by using the iPhone 6s and Pixel 2 are both less than 0.08 mm. The mean errors of the JRC are −7.54 and −5.27% with point intervals of 0.25 and 1.0 mm, respectively. The smartphone SfM photogrammetric method has comparable accuracy to a 3D laser scanner approach for reconstructing laboratory-sized rock joint surfaces, and it has the potential to become a popular method for measuring rock joint surfaces.

show abstract

Section: Methodsmentioning

confidence: 99%

Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry

Fang

Jiang

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Considering the design factors of on-site blasting and the actual situation on site, the blasting design parameters (A 1 ), rock characteristic parameters (A 2 ), and performance parameters of explosives (A 3 ) are selected as the criterion layers of AHP; A 1 include the quantity of blasthole (N), hole spacing (S), hole depth (H), powder factor (P), minimum resistance line (B), and maximum explosive per hole (Q). Rock compressive strength (τ) and rock tensile strength (σ) are the main parameters that can represent rock properties [23,24]. Meanwhile, detonation velocity (D), explosive action capacity (W), and detonation pressure (C) are selected as the factor layer of A 3 .…”

Section: Quantification Of Blasting Parametersmentioning

confidence: 99%

Control of Rock Block Fragmentation Based on the Optimization of Shaft Blasting Parameters

Luo

Huang

et al. 2020

Geofluids

Self Cite

View full text Add to dashboard Cite

In the construction of shaft, the blockage of the mucking shaft may cause the mud-water inrush disaster. Oversized rock fragmentation is the main cause for the blockage of the mucking shaft in the raise boring machine (RBM) construction method. The influence degree of blasting parameters on rock fragmentation after blasting is quantified by adopting analytic hierarchy process (AHP). On this basis, the shaft blasting maximum rock fragmentation control model based on double hidden layer BP neural network is proposed. Results show that the maximum rock fragmentation discharged from the mucking shaft after blasting should not exceed 1/3 of the diameter of the slag chute. The influence weight of the minimum resistance line that accounts to 15.6%, when AHP is applied for the quantification of the blasting parameters, can be regarded as the most important blasting parameter. The average absolute errors between the predicted value and the actual value of the largest block size control model of the shaft blasting are only 2.6%. The inversion analysis of the model can rapidly obtain the required blasting parameters, which can be used to guide the construction of the tunnel ventilation shaft.

show abstract

“…However, two-dimensional joint surfaces are different with three-dimensional natural rock joints. Given that abundant real rock joints with the same surface are difficult to obtained in the past, plenty of replica joints made of mortar, cement, plaster or other similar materials are mainly used in direct shear tests to explore the shear behaviour of rock joints (Tang et al 2016;Huang et al 2020;Liu et al 2020;Huan et al 2023). However, similar materials would just be ideal for modelling rock joints with low to medium strength (Jafari et al 2004), while they cannot replace actual hard rock joints (Ban et al 2023).…”

Section: Introductionmentioning

confidence: 99%

Shear behaviour of different joints and its influence on fault slip rockburst using 3D printing and 3D carving

Cheng,

Zhang

2024

Preprint

View full text Add to dashboard Cite

Rock joints are widely distributed in rock masses, and their mechanical behaviours largely determine the strength and stability of the rock mass. The shear slip and failure along weak joints can lead to the instability of the rock mass and even induce landslides, tunnel collapses, rockbursts or other geological disasters. Thus, the study on the shear behaviours of rock joints and their influence on rockbursts is very important for the prevention of rockbursts and the safe construction of tunnels. In this paper, three types of rock joints (plaster mortar joints, marble joints and granite joints) containing the same surface are reproduced applying the 3D printing and 3D carving techniques. Shear tests of three different rock joints are performed under different normal stress levels. The shear behaviours and acoustic emission (AE) characteristics of different rock joints and their influence on fault slip rockbursts are addressed. The results indicate that the sudden stick slip and violent stress drops of granite joints could release enormous amounts of energy, which is more likely to induce a fault slip rockburst. The stress drop values after the peak increase with increasing applied normal stresses, resulting in an increase in the possibility of fault slip rockbursts. Dynamic shear failure dominates in granite joints, and the corresponding AE energy rate generated during shearing is also higher than that of the other two joints, indicating that more energy is released and that fault slip rockbursts occur easily.

show abstract

Experimental Technology for the Shear Strength of the Series-Scale Rock Joint Model

Cited by 36 publications

References 41 publications

Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry

Measurement of Rock Joint Surfaces by Using Smartphone Structure from Motion (SfM) Photogrammetry

Control of Rock Block Fragmentation Based on the Optimization of Shaft Blasting Parameters

Shear behaviour of different joints and its influence on fault slip rockburst using 3D printing and 3D carving

Contact Info

Product

Resources

About