Rock Strength Parameters Research Articles

A geometric variation method to extract rock strength parameters via uniaxial compression testing

Numerical modelling in rock engineering and mechanics often requires inputting multiple sets of strength parameters, such as the commonly encountered tensile strength, cohesion, and friction angle. Usually, obtaining these parameters requires performing different types of rock mechanics experiments on certain rock specimens, such as tension tests and triaxial tests, which are time-consuming and labor-intensive. Uniaxial compression testing is simpler and requires less demanding equipment. This paper proposes a solution that relies solely on uniaxial compression testing to obtain multiple sets of rock strength parameters. The basic idea is to treat the process of acquiring multiple parameters as a problem of solving a set of mathematical equations. The uniaxial tests with different geometric specimens provide known quantities and the corresponding equations that link these known quantities (e.g., peak loads) with unknown quantities (e.g., strength parameters). We established three-dimensional numerical tests to represent the relationship between input strength parameters and the peak load. By transforming it into an optimization problem, numerical modelling is embedded into the objective function of the optimization algorithm, thereby achieving the automatic extraction of strength parameters. This method is verified through uniaxial compression tests using red sandstone specimens with various geometries. The results show that by changing the geometry of the rock specimens, multiple sets of strength parameters can be obtained. These parameters are successfully used to predict (extrapolate) peak loads of other geometric specimens. This method holds promise for achieving the automated extraction of material parameters for the numerical modelling of rock.

Research on rockburst proneness evaluation based on interpretation of drilling parameters

Rockburst is one of the common geological disasters in underground engineering. Rockburst proneness evaluation is the premise of rockburst disaster prevention and control. It is an effective method to evaluate rockburst proneness by brittleness index. The traditional brittleness index testing requires coring the surrounding rock in the field and transporting it to the laboratory for testing. The testing process is inefficient and disconnected from the in-situ environment. The effective in-situ and accurate test of brittleness index has become a challenge. Digital drilling testing of rock mass is a new approach to solve the above problems and future research direction. The study explore a rockburst proneness evaluation method based on the interpretation of real-time drilling parameters. The key of this method is to establish the quantitative relationship model between the brittleness index and drilling parameters. Digital drilling tests on different rock types were conducted using the rock intelligent rotary cutting testing system (RCT system). The quantitative relationship between drilling parameters and rock strength parameters was analyzed. The drilling test model of rock equivalent brittleness index (DP-EBI model) is established. The verification test results show that the difference rate between the rock brittleness index with drilling test and indoor test is 11.8%. On this basis, the testing results of five rockburst evaluation methods, including equivalent brittleness index EBI, energy impact index ACF, potential energy of elastic strain PES, brittleness index modified BIM and dynamic failure time DT were compared. The effectiveness of using drilling parameters to evaluate rockburst proneness is verified. This study can provide a theoretical and methodological basis for the in-situ detection and evaluation of rockburst proneness and grade in underground engineering fields, such as mine roadways, transportation tunnels, and hydraulic tunnels.

Probabilistic back analysis of rock strength parameters in heavily jointed rock slopes based on Bayesian inference

Probabilistic back analysis of rock strength parameters in heavily jointed rock slopes based on Bayesian inference

Detection methods for strength deterioration and structural characteristics of fractured rock based on digital drilling

Fractures ubiquitously exist in strata, and large-scale fractures can cause low bearing capacity and poor stability in rock masses and can sometimes lead to hazards such as roof falls and collapses in mines and tunnels. The foundation of the control of surrounding rocks and effective prevention of such hazards is to be able to accurately determine the structural characteristics of fractures and strength parameters of rocks. Traditionally, testing is carried out mainly through indoor compression tests and borehole inspection, which require drilling of the surrounding rock on site and core testing indoors. The effective in situ and accurate detection of the structure and strength properties of surrounding rock has become a challenge. Digital drilling testing of rock mass is a new approach to solve the above problems and future research direction. In this study, a multifunctional rock mass digital drilling test system is used to perform tests on different types of fractured rocks. The response of drilling parameters to fracture parameters is analysed, and a strength deterioration evaluation index for fractured rock based on drilling parameters is established. Then, the response mechanism of the strength deterioration rate while drilling in the fracture zone is defined, and a model for identifying fracture parameters based on drilling is established. Furthermore, an in situ detection method for fractured rock properties based on digital drilling is proposed. The results of the validation test show that the average difference ratio between the equivalent compressive strength measured by the drilling test and the laboratory compressive test is 3.97 %. The strength degradation of the fractured rock is significant, with a maximum strength degradation rate of 82.1 % obtained through drilling. The average identification accuracies of the fracture position and width are 2.56 mm and 0.85 mm, respectively. The identification accuracy of rock properties while drilling is high, which proves the effectiveness of the prediction model while drilling. This study can provide a theoretical and methodological basis for the accurate in situ prediction of rock properties in underground engineering fields, such as mine roadways, transportation tunnels, and hydraulic tunnels.

Spatial Variations of Deformation along a Strike-Slip Fault: A Case Study of Xianshuihe Fault Zone, Southwest China

The distribution of damage zones around a fault has long been regarded as a frontier and hot spot in the field of geoscience but is still not fully understood. In this study, we conducted field investigations and tests around the Xianshuihe fault zone (XSHF), a left-lateral strike-slip fault with a length of about 400 km located in the eastern margin of the Tibetan Plateau. The results reveal that the fracture frequency and rock strength parameters present a spatially asymmetric distribution along the fault and have a negative power-law correlation with the distance from the fault. The widths of the damage zones are approximately 20.8 km and 17.1 km in the southwest and northeast directions, respectively. Combined with the previous studies, we presented a negative power-law function to depict the correlation between slip displacement and the width of the damage zone and found that the growth rate of damage zone in faults with low displacement is greater than that in those with large displacement. The study demonstrates that the asymmetric distribution of the damage zone surrounding the XSHF is mainly due to the stress redistribution in different damage zones stemming from the left echelon and different activity rates of the blocks on both sides of the XSHF.

Empirical design for the excavation method and support system at Budong-Budong Dam Diversion Tunnel, Central Mamuju, West Sulawesi Province

Budong-Budong Dam, located in the West Sulawesi Province of Indonesia, was designed to use a tunnel to divert river flow during the dam construction. The Rock Mass Rating was used to examine the tunnel design with a less detailed drill core investigation. The rock strength parameter is only based on the field estimation. The entire diversion tunnel will pass through Breccia with weak strength. Evaluation is required using integrated and precise data to guarantee safety during and post-construction. The RMR classification was used to determine the excavation and preliminary tunnel support, while the Q-System was used to compare the support of the tunnel. Those classifications were used to anticipate the geological conditions uncertainty. Geological data were collected by geological mapping, evaluation of subsurface drilling, and laboratory analysis. The tunnel will pass through a Tuffaceous Breccia and Tuffaceous Sandstone insert of Tuffaceous Siltstone. In addition, a poor-quality rock was found around the inlet and outlet, and a fair-quality rock in the middle of the tunnel. Hence, drilling and blasting were recommended for the excavation. The tunnel’s proposed support system included shotcrete, wire mesh, and rock bolts in the middle of the tunnel. Steel sets are added around the inlet and outlet.

Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces. In tunneling practice, the rock mass quality is often assessed via a combination of qualitative and quantitative parameters. However, due to the harsh on-site construction conditions, it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction. In this study, a novel improved Swin Transformer is proposed to detect, segment, and quantify rock mass characteristic parameters such as water leakage, fractures, weak interlayers. The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%, 81%, and 86% for water leakage, fractures, and weak interlayers, respectively. A multi-source rock tunnel face characteristic (RTFC) dataset includes 11 parameters for predicting rock mass quality is established. Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset, a novel tree-augmented naive Bayesian network (BN) is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%. In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset. By utilizing the established BN, a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters, results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

Evaluation of Jacking Forces in Weathered Phyllite Based on In Situ Pressuremeter Testing and Deep Learning

Pipe jacking is a trenchless technology used to install buried pipelines, such as sewer lines in wastewater management systems. Existing mechanistic approaches based on geomaterial strength parameters (i.e., friction angle and apparent cohesion) can provide an estimation of the potential jacking forces during construction. However, extracting intact rock cores for strength characterisation is challenging when dealing with highly weathered ‘soft rocks’ which exhibit RQD values of zero. Such was the case for a pipe jacking drive traversing the highly weathered lithology underlying Kuching City, Malaysia. Furthermore, mechanistic approaches face limitations during construction when jacking forces are dependent on operation parameters, such as jacking speed and lubrication. To address these knowledge gaps, the primary objectives of this study are the development of rock strength parameters based on in situ pressuremeter testing for the purpose of estimating jacking forces. Furthermore, this study investigates the influence of various pipe jacking operation parameters, with a particular focus on their impact on jacking forces in weathered ‘soft rocks’. To achieve this, a novel deep learning model with an attention mechanism is introduced. The proposed methods of rock strength parameters derived from pressuremeter testing and the utilisation of deep learning will help to provide insights into the key factors affecting the development of jacking forces. This paper successfully shows the use of in situ pressuremeter testing in developing Mohr–Coulomb (MC) parameters directly from the site. In addition, the developed deep learning model with an attention mechanism successfully highlights the significance of pipe jacking operation parameters with an accuracy of 88% in predicting the jacking forces.

Intelligent real-time perception method for rock strength based on vibration and power fusion characteristics

To improve the sensing accuracy of rock strength parameters, a method based on the fusion of vibration response and electrical response is proposed. Firstly, multi-layer noise reduction based on local mean decomposition is carried out for vibration response, and the product function containing exceeds 85% of the original information is selected by the multi-index comprehensive decision method, and the wavelet threshold denoising is used as the pre-processing unit of singular value decomposition. Next, the multi-domain feature extraction and KPCA are carried out for vibration signal after noise reduction to construct fusion feature vectors. Also, the statistical characteristics of the electrical parameters are extracted and fused with the fusion features. Finally, multi-source information is input into the least squares support vector machine model optimized by the improved whale algorithm to perceive the rock strength parameters. The experimental results show that the sensing accuracy of the proposed method is the highest (96.875%) compared with the single information while drilling and the traditional prediction method, which verifies the superiority of the proposed method.

The research of the phosphogypsum granulometric composition and the patterns of its reconstitution in the aggradiational waste disposals

The mechanical characteristics of the stocked into dump massives dispersed rocks influencing the slope stability is strongly determined by slopes’ granulometric composition. Due to the phosphogypsum specific characterics, it may be difficult to choose the proper methodology for its’ granulometric composition studying. This article is dedicated to the comparative analysis of the results of the different methods’ usage for granulometric composition of this material in the aggradiational waste disposals research. Additionally the problem of aggradiational phosphogypsum homogeneity in such structures has also been studied by determining the presence of fractionation and rock strength parameters’ in the ash pond beach variability.

К ВОПРОСУ ОПРЕДЕЛЕНИЯ ЗНАЧЕНИЙ СЦЕПЛЕНИЯ И УГЛА ВНУТРЕННЕГО ТРЕНИЯ ГОРНЫХ ПОРОД

The paper analyses the strength parameters of rocks tested under uniaxial and volumetric stress states. Based on their results, the Mohr stress limit circles and their envelope line were plotted in the field of tangential and normal stresses. According to its slope and intersection with the tangent stress axis, the cohesion (C) and the angle of internal friction (φ) were determined. Calculated, using the values (C and φ), strength in uniaxial compression was higher than the actual strength by 20 and more per cent. It is suggested to change the methodology of determination of adhesion and angle of internal friction. It is proposed to determine them not by the envelope of the limiting circles of Mohr stresses line, but by the change of limiting values of tangential stresses of Mohr's circles from normal stresses.

Numerical Analysis of the Shape Effect on the Mechanical Behaviors of Rocks in True 3D Compression Test

Rock strength parameters are usually indispensable for rock engineering design. Under the experimental testing conditions, the shape effect could significantly affect the measured results. Previous findings from uniaxial tests reveal that the measured rock strength gradually decreases with the increase in the slenderness ratio, which is mainly ascribed to the end effect. However, it is still unclear how strong the influence of the end effect on the shape effect is in true 3D tests. In the present study, rock mechanical behaviors in response to the variation in slenderness ratio are detailly examined in true 3D tests. The calculated results show that rock strength progressively decreases as the slenderness ratio increases. But the rock strength in true 3D tests still deviates far from the actual even though the slenderness ratio goes beyond 2, which is mainly caused by the interface friction along the two extra σ2-normal specimen faces. It is interesting that the slenderness ratio increases lead to an increase in the measured stiffness as well. The calculated results suggest that symmetry in the experimentally defined typical arc-shaped curves σ1(σ2) at constant σ3 are neglected most likely due to the stronger end effects in true 3D tests, and the accurate rock strength parameters are not obtained only through using slender specimens.

Determination of regions prone to sand production and the linkage to fluid flow rates by integrating rock strength parameters and microphotographs in the southern onshore basin, India

One of the main challenges for healthy hydrocarbon yields from the production wells is the sand production, and its control assumes significant importance for successful production operations. The prime objective remains to control the sand production without compromising on the fluid flow rates. Sand production is conventionally associated with diverse heterogeneous formations, especially poorly consolidated formations. Scrutinizing fluid flow rates at different orientations of perforations is a valuable analysis in controlling the sand production. This study was conducted to examine the case of sand production in a few development wells from Malleshwaram field of the Krishna Godavari (KG) basin in south India and provide alternatives to arrest this sand production. The influence of oriented perforations on fluid flow rates to minimize sanding tendencies was examined. Sand grain diameter was estimated using the distribution plots of the grain sizes obtained from the photomicrographs, and the average value of the grain size was estimated around 100 μm. The fluid flow model was simulated for actual scenario in the hydrocarbon bearing Nandigama formation using finite element modeling (FEM). Sanding tendencies in these formations were studied at varying depletion rates. Critical draw down pressure (CDDP), which is a function of both critical bottom hole pressure and reservoir pore pressure, for well 1 and well 2 is estimated as 4650 Psi and 3400 Psi, respectively, at 0% depletion. CDDP was used to estimate the onset of sanding, and the flow rate for horizontal perforation was calculated as 0.024548 m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathrm{m}}^{3}$$\\end{document}/sec. Strength parameters, namely the unconfined compressive strength (UCS) and cohesion, were also investigated in all the wells to decipher the formation strength and a possible linkage to sanding. These results present a completely fresh analysis of the sanding potential and the related parameters responsible for it in these formations. Fluid flow rates for the producing reservoir are studied at different set of oriented and sized perforations. It was observed that a hiked flow rate in horizontal perforations maintains the production in a safe and no-sanding zone. This study provides vital information and a workflow for similar heterogeneous complex formations for designing the well completions, augmenting economic production and reinforcing future reservoir management.

Overview of the Empirical Relations between Different Aggregate Degradation Values and Rock Strength Parameters

The aggregates are essential materials in civil engineering, they are used for railway and road constructions, for hydraulic engineering but they are also the base material of concrete. The crushed stones are exposed to several effects during their lifespan. Therefore, several tests were developed to evaluate their performance. One of the most important aspects is the resistance to degradation. However, degradation tests require special types of equipment and usually take longer than common strength tests which are more likely to be available for rock materials. Therefore, the empirical connections between strength and degradation values can be extremely useful in practice. The paper aimed to collect all available relationships and datasets from the literature that presents the relations between these different parameters – such as Aggregate Impact Value (AIV), Aggregate Crushing Value (ACV), Ten Percent Fines Value (TFV), Los Angeles Abrasion Value (LAAV), and micro-Deval Coefficient (MDE) – and rock strength parameters – such as Uniaxial Compressive Strength (UCS) and Point Load Strength Index (IS(50)) – and to provide the best-fit formula for different rock types. The paper also highlights the difficulties and limitations of the compared relationships.

Probabilistic prediction of uniaxial compressive strength for rocks from sparse data using Bayesian Gaussian process regression with Synthetic Minority Oversampling Technique (SMOTE)

Uniaxial compressive strength (UCS) of rocks is one of key rock strength parameters. Generally speaking, UCS can be measured directly through uniaxial compression tests, which is often unfeasible, especially when intact rock samples are highly fragile. Alternatively, the UCS of rocks can be estimated indirectly from other easily available rock indices. Note that adequate measurement data is the prerequisite for the accurate estimation of UCS using indirect methods. This may be difficult to achieve due to the limitation of time and budget, especially for small- to medium-sized projects. In this case, it becomes a challenging issue on how to develop a robust and reliable model for UCS estimation using the sparse measurement data. A fully Bayesian Gaussian process regression (fB-GPR) approach with Synthetic Minority Oversampling Technique (SMOTE) is proposed in this paper to address this problem. A real-life example from Malaysia was used for illustration and validation of proposed method. Results showed that when the synthetic sample size in SMOTE reaches 30 (i.e., optimal synthetic sample size), the coefficient of determination (R2) increases by about 18.92%, and the accuracy of feature selection reaches 98%, compared with the scenario with only sparse measurement data used for fB-GPR model development.

A new method for determining strength parameters of rock using digital drilling technology

Fast and accurate prediction for mechanical parameters of rock mass is an important prerequisite for guiding the safe construction of rock engineering. At present, the rock strength parameters test requires well-prepared samples; sample preparation is time consuming, costly, and difficult as well as destructive, in particular the polishing and rectification of the sample ends. In this paper, the mathematical model of the drilling process is established based on the force characteristics of the drill bit and the principle of mechanical limit equilibrium. The digital drilling tests are carried out on four types of rocks to drilling characteristics using the digital drilling system. The concept of cutting strength ratio is proposed to analyze the correlation between cutting strength ratio and rock internal friction angle and cohesion. A new method is proposed for determining the compressive and tensile strength of rock. The results show that the cutting strength ratio increases with the increasing of internal friction angle and cohesion. The uniaxial compressive strength and tensile strength of rock increase linearly with the cutting strength ratio. The average error of rock tensile strength is 12.29%, and the average error of uniaxial compressive strength is 20.44%. The internal friction angle of rock obtained based on the digital drilling technology is consistent with the value measured by the laboratory standard test. This method can provide a new way to determine rock strength parameters in real time.

Failure mechanism of large-scale landslide in the central Nepal Himalaya

The geomorphological and geological characteristics of central Nepal reflect the dynamic nature of tectonic and mass movement processes that lead to the occurrence of large-scale landslides (LSLs). The mechanism of the LSL failure process is not well understood due to the different deformation stages controlled by geological structures and causative/ triggering factors. Regional tectonic structures and local rock mass characteristics play a vital role in the formation of LSLs. Engineering geological characterization was performed to evaluate the rock/soil properties, and the associated state of danger (cracks, seepage, etc.). The rock mass rating (RMR) and geological strength index (GSI) methods were used to estimate rock mass quality and strength parameters. The estimated strength parameters together with laboratory test data were used to set up a two-dimensional (2D) landslide surface to simulate the failure scenarios. The simulation of landslide models was iterated under different loading conditions by incorporating geological heterogeneities. The results have demonstrated that the movement of the slope was affected by different stress conditions over time, which were verified using spatiotemporal landslide data. The landslide exhibited a three-stage failure mechanism with the development of tension-induced cracking at the rear and shearing failure of the critical locking section in the middle section. The tension shear and joint-step-path rupture along joint surfaces occurred during different stages of the landslide failure processes. The simulated results showed that the genetic development of LSL is mainly attributed to the geological structures and sudden changes in stress conditions. Thus, the research outcomes can be illustrative to evaluate the role of geological discontinuities, geotechnical parameters and triggering effects by the numerical simulation techniques for the failure mechanism of LSLs.

Two-dimensional face stability analysis in rock masses governed by the Hoek-Brown strength criterion with a new multi-horn mechanism

The face stability problem is a major concern for tunnels excavated in rock masses governed by the Hoek-Brown strength criterion. To provide an accurate prediction for the theoretical solution of the critical face pressure, this study adopts the piecewise linear method (PLM) to account for the nonlinearity of the strength envelope and proposes a new multi-horn rotational mechanism based on the Hoek-Brown strength criterion and the associative flow rule. The analytical solution of critical support pressure is derived from the energy-work balance equation in the framework of the plastic limit theorem; it is formulated as a multivariable nonlinear optimization problem relying on 2m dependent variables (m is the number of segments). Meanwhile, two classic linearized measures, the generalized tangential technique (GTT) and equivalent Mohr-Coulomb parameters method (EMM), are incorporated into the analysis for comparison. Surprisingly, the parametric study indicates a significant improvement in support pressure by up to 13% compared with the GTT, and as expected, the stability of the tunnel face is greatly influenced by the rock strength parameters. The stress distribution on the rupture surface is calculated to gain an intuitive understanding of the failure at the limit state. Although the limit analysis is incapable of calculating the true stress distribution in rock masses, a rough approximation of the stress vector on the rupture surface is permitted. In the end, sets of normalized face pressure are provided in the form of charts for a quick assessment of face stability in rock masses.

Numerical simulation of rock-breaking mechanisms by triple-ridged PDC cutter in hard rocks

As basic cutting element of PDC bit, PDC cutters play crucial roles in breaking rocks for PDC bit. Conventional PDC cutter usually gets broken when drilling into deep formations due to high hardness and strong abrasion. To help solve such a problem, triple-ridged PDC cutters have been developed and utilized in the design of hybrid-cutters PDC bit, which have achieved enhanced rate of penetration and high life cycle. Nevertheless, few researches have focused on the rock-breaking mechanisms of triple-ridged PDC cutter. Thus, this research carries out a series of numerical simulations to reveal the rock-breaking mechanisms of the triple-ridged PDC cutter. The numerical analysis and the visualization of the rock-breaking process are shown in the paper. Parametrical analyses have also been conducted to reveal effects of cutting parameters, rock strength, and cutter structural parameters on the rock-breaking performances of the triple-ridged PDC cutter. Numerical results show that the triple-ridged PDC cutter is more easily to break the rock than the conventional PDC cutter by combining the shearing and the crushing effects, predominantly leading to much smaller cutting force. Given the same cutting depth and the cutting angle, the triple-ridged PDC cutter can exhibit higher rock-breaking efficiency than that of the conventional PDC cutter. Also, optimal analysis should be done for the structural design of the triple-ridged PDC cutter. These research findings help the readers understand the rock-breaking mechanisms and the further application of the triple-ridged PDC cutter in deep hard formations.

Reliability analysis of rock slopes considering the uncertainty of joint spatial distributions

To reasonably and effectively evaluate the stability of jointed rock slopes, this study proposes a reliability analysis method that considers the uncertainty of the joint spatial distribution. First, the discrete fracture network (DFN) model is used to characterize the variability of joint geometric parameters, and a random variable of joint location is assumed to be a random integer that follows a uniform distribution in the random number library. Then, Latin hypercube sampling is used to sample uncertain random variables to generate random numbers, and construct the corresponding DFN model. Finally, the safety factor (Fs) of each numerical model under sampling is calculated by strength reduction method, and the failure probability of jointed rock slope is obtained by statistical analysis of Fs. The comparative analysis results demonstrate that considering the uncertainty of joint spatial distribution is crucial for accurately analyzing the reliability of rock slopes. This method comprehensively considers the main internal factors that affect the reliability of jointed rock slopes, including the uncertainty of rock strength parameters and variability of geometrical parameter and the location randomness of joints, making the results of the evaluation of the reliability of rock slopes more precise and reasonable.