Mass Discontinuity Research Articles

On the use of semi-georeferenced photogrammetric dense point clouds in the investigation of rock mass discontinuity properties

On the use of semi-georeferenced photogrammetric dense point clouds in the investigation of rock mass discontinuity properties

Resonant transport in a double-barrier heterostructure AlxGa1−xAs/GaAs and mass discontinuity: a semiclassical path integral approach

In this paper, we investigate the dependence of the resonant carrier transport in an AlGaAs/GaAs double-barrier heterostructure on the electron’s effective mass discontinuity between the well and the barrier layer. We use a one-dimensional model for the effective potential and consider the activation of the resonant tunneling mechanism when a bias is applied between the emitter and the collector. We calculate the system’s Green’s function through semiclassical path integration to obtain the complex spectrum. Electron’s effective mass discontinuity affects our calculations through the contributions of the various propagations inside the heterostructure and the multiple reflections from the turning points. Our findings show that the lowest resonance energy decreases linearly with increasing bias, while the real energy shift of the resonance decreases in a non-linear manner with the mass discontinuity. We also observe that the resonant transport time increases nearly linearly with the mass discontinuity. These results demonstrate the impact of the carrier’s inertia enhancement on the resonance characteristics and are consistent with established concepts in quantum mechanics and previously published works. Furthermore, we identify a critical bias value that distinguishes the behavior of the symmetric and asymmetric heterostructure. Additionally, the derivative of the transport time with respect to mass discontinuity is found to be independent of the applied bias. Our results provide concise analytical relationships involving parameters such as barrier and well thickness and shape, enabling the prediction and optimization of various nanoscale devices’ performance.

II-LA-KM: Improved Initialization of a Learning-Augmented Clustering Algorithm for Effective Rock Discontinuity Grouping

Rock mass discontinuities are an excellent information set for reflecting the geometric, spatial, and physical properties of the rock mass. Using clustering algorithms to analyze them is a significant way to select advantageous orientations of structural surfaces and provide a scientific theoretical basis for other rock mass engineering research. Traditional clustering algorithms often suffer from sensitivity to initialization and lack practical applicability, as discontinuity data are typically rough, low-precision, and unlabeled. Confronting these challenges, II-LA-KM, a learning-augmented clustering algorithm with improved initialization for rock discontinuity grouping, is proposed. Our method begins with heuristically selecting initial centers to ensure they are well-separated. Then, optimal transport is used to adjust these centers, minimizing the transport cost between them and other points. To enhance fault tolerance, a learning-augmented algorithm is integrated that iteratively reduces clustering costs, refining the initial results toward optimal clustering. Extensive experiments on a simulated artificial dataset and a real dataset from Woxi, Hunan, China, featuring both orientational and non-orientational attributes, demonstrate the effectiveness of II-LA-KM. The algorithm achieves a 97.5% accuracy on the artificial dataset and successfully differentiates between overlapping groups. Its performance is even more pronounced on the real dataset, underscoring its robustness for handling complex and noisy data. These strengths make our approach highly beneficial for practical rock discontinuity grouping applications.

Semi-supervised recognition of tunnel surrounding rock discontinuities using drilling jumbo data

Geological information ahead of the tunnel face is vital for ensuring safe and efficient tunnel construction. This paper presents a semi-supervised approach that combines a constrained dense convolutional autoencoder (CDAE) with a hybrid deep neural network (HDNN) to predict rock mass discontinuities. The factors related to rock mass discontinuity are categorized into four main classes: geometry, geology, construction, and measurement while drilling (MWD). The geological similarity between neighbouring blastholes is taken into consideration to constrain the training process of CDAE. These four categories of data serve as input parameters for CDAE-HDNN to predict rock mass discontinuity. Data from the Yangjiawopu tunnel is employed to assess the performance and generalization capability of the proposed method. The results show that CDAE can extract features related to rock mass discontinuity, and the proposed model exhibits superior performance and robustness compared to conventional deep learning and machine learning models.

The Laser Scanner Technique: A Tool for Determining Shear Strength Parameters of Rock Mass Discontinuities

When evaluating the shear strength of rock mass discontinuities, certain challenges arise due to the difficulty in quantifying the roughness characteristics of surfaces and the strength of asperities. Recent research has focused on enhancing techniques for assessing these characteristics and exploring the application of laser scanning to aid in evaluating discontinuity features. The analysis of reflectivity values (I) obtained through a laser scanner survey presents an efficient method for assessing mechanical characteristics, such as joint compressive strength (JCS). Reflectivity measurements demonstrate correlations with Schmidt hammer rebound values (r). The laser scanner technique would enable the measurement of JCS without the direct application of the Schmidt hammer on rocks in areas where rebound values (r) measurements are unavailable. The use of a laser scanner allows for the acquisition of high-precision geometrical information concerning the 3D roughness and anisotropy of rock surfaces. In this study, an innovative technique was introduced that utilizes laser scanner data from six previous experimental surveys conducted on rock formations in Southern Italy. This technique facilitates the evaluation of roughness profiles, considering potential variations along kinematically admissible sliding directions, allowing for the estimation of the Joint Roughness Coefficient (JRC). This new methodology aids in evaluating the parameters of Barton’s equation to determine the strength characteristics of rock mass discontinuities.

A new method to automatically identify and characterize rock mass discontinuities using a smartphone: Experiences from a slope and a tunnel

Smartphones equipped with high-resolution lenses and advanced photo processing capabilities have evolved into versatile, multifunctional devices. This paper introduces a novel method for extracting and analyzing rock mass discontinuities using smartphones, encompassing smartphone photography, ground control point selection, point cloud reconstruction, and discontinuity set identification and analysis. The method was validated through a slope case study in Bayi District, Linzhi city, Tibet, China, under natural light and a tunnel case study in Northwest China under artificial light, and the results agreed well with traditional compass measurements. Notably, the method proved efficient, reducing the measurement time to 15 min compared to 1.5 h with a geological compass in Case 1. Significant insights were gained regarding the impact of photo quantity and shooting distance on point cloud accuracy, along with the influence of lighting in tunnel environments, thus offering valuable guidance for fieldwork. Moreover, the potential of this smartphone-based method was confirmed through comparative analysis with laser scanner data. In summary, rock mass measurements using smartphones are validated as simple, efficient, and practical approaches for geological studies.

A Novel Rock Mass Discontinuity Detection Approach with CNNs and Multi-View Image Augmentation

A Novel Rock Mass Discontinuity Detection Approach with CNNs and Multi-View Image Augmentation

The use of digital technology for rock mass discontinuity mapping: review of benchmarking exercise

The use of digital technology for rock mass discontinuity mapping: review of benchmarking exercise

Investigating the influence of discontinuity parameters on blast-induced fragmentation

ABSTRACT Fragmentation by blasting is a critical process in hard rock mining. The interaction between the rock mass and blast energy influences the outcomes, specifically on the rock mass response to higher stresses and loading rates, and the properties of structures. In this study, LS-DYNA is used to model the nonlinear dynamic fracturing of the rock to understand the effects of rock mass properties on the blast outcomes. The results are verified and compared with the case study, and they show that the formation of damage zones around the charge is highly influenced by rock mass strength and discontinuity properties.

Semi-automatic recognition of rock mass discontinuity based on 3D point clouds

Information on rock mass discontinuities is crucial for rock mass stability analysis. Due to the low efficiency, incompleteness, and potential risk of the traditional compass methods in measuring discontinuities, three-dimensional light detection, ranging, and other remote sensing methods have become essential. In this study, voxel filtering was used to subsample a point cloud so that its feature points were retained while reducing the computational load. An improved regional growing (RG) algorithm was then used to extract rock mass discontinuities. A software Geocloud v1.0 was developed based on the proposed method to semi-automatically recognize discontinuities. Additionally, two groups of sensitivity experiments were performed to analyze the influence of different numbers of nearest neighbors and maximum RG angles on the extraction of discontinuities. Results showed that most of the discontinuities could be accurately recognized with different thresholds. Furthermore, the accuracy of the proposed method was verified by real geometries, on a real highway slope, and in a natural quarry. Finally, the efficiency of the proposed method was proven using comparative computational experiments.

Sparrow search algorithm-driven clustering analysis of rock mass discontinuity sets

Sparrow search algorithm-driven clustering analysis of rock mass discontinuity sets

Identification of rock mass discontinuity from 3D point clouds using improved fuzzy C-means and convolutional neural network

Identification of rock mass discontinuity from 3D point clouds using improved fuzzy C-means and convolutional neural network

Slope Design in Surface Mining with a Total Probability Methodology [Diseño de Taludes en Minería Superficial con una Metodología de Probabilidad Total

The main goal of this research is to propose a methodology for the design of optimal slopes in surface mining, by applying the probability of total failure in the process of determining the geometry of the berm-bench of rock slopes. The rock mass is characterized by being a discontinuous, anisotropic and random medium. Therefore, to design slopes, a deterministic value or Safety Factor that represents the reliability of the design is not sufficient, and the inherent uncertainty of the geotechnical properties must be considered. The stability of slopes at bench level is a function of the quality of the rock mass and is controlled by the strength of the intact rock, the structural rocks, or a combination of both. When the slope has a defined structural control, planar, wedge or toppling failure modes are formed; These, depending on the stability conditions and generates rockfall events. Therefore, it is necessary to apply an effective method to establish the optimal geometry of the bench. The purpose of the berm-bench is to retain and mitigate the risk of rockfall and contain spill from upper slopes due to inherent instabilities, to provide a safe environment for personnel and equipment working near the slopes. The proposed methodology considers the variability of the dip, dip direction, persistence, and friction of the discontinuities. The procedure begins with the collection and analysis of the geotechnical information of the rock mass, which defines geotechnical domains, design sectors and main families of discontinuities; then, statistical analysis and kinematic evaluation are carried out and the conceptual berm width is determined; finally, the kinetic and probability of total failure analysis is carried out, validating the design geometry. The research focused on a domain with 04 sectors of geotechnical design. The results show that the applicable design bench face angle is between 53° and 71°, which corresponds to a berm width of 9.3m to 8.6m and a geometric interramp angle between 36° and 48° respectively. Likewise, probabilities of total planar failure of up to 31% and total wedge of 41% were obtained according to the geotechnical peculiarities of each sector. It was proven that, in the sectors with a greater probability of failure, a lower bench face angle and a greater catch bench of the design berm are considered acceptable designs, due to a greater probability of crest loss. Finally, in the sectors with a lower probability of failure, a greater interramp angle is considered an acceptable design. In conclusion, through the applied methodology it has been demonstrated that the results of the berm-bench design process meet the acceptability criteria of the Probability of Failure. Therefore, the developed method, which considers the variability of the parameters of the rock mass discontinuities, allows designing safe and reliable slopes validated through an acceptable level of probability.

New method to identify optimal discontinuity set number of rock tunnel excavation face orientation based on Fisher mixed evaluation

Discontinuity is critical for strength, deformability, and permeability of rock mass. Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping. Traditional methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes, which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of evaluation. This paper proposes a new method of Fisher mixed evaluation (FME) to identify optimal group numbers of rock mass discontinuity orientation. In FME, orientation distribution is regarded as the superposition of Fisher mixed distributions. Optimal grouping results are identified by considering the fitting accuracy of Fisher mixed distributions, the probability monopoly and central location significance of independent Fisher centers. A Halley-Expectation-Maximization (EM) algorithm is derived to achieve an automatic fitting of Fisher mixed distribution. Three real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity grouping. Four clustering validity indexes are used to automatically identify optimal group numbers for comparison. The results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.

A method for analyzing discontinuities characterization using the integration of underground drift point cloud with 3DEC software

The geometric statistical characteristics of rock mass discontinuities, such as mean trace length and intensity, cannot be measured directly and require the use of statistical tools (such as sampling lines, sampling windows, and drilling) for analysis. In this paper, we propose a method for extracting discontinuity characteristics using the 3DEC software in three-dimensional (3D) drift models (3DM). Specifically, we introduce the Surface Disk Discontinuity Model (SDDM) as a representation model for planar and linear discontinuities identified in point clouds. By importing the 3DM and SDDM into 3DEC and utilizing a multi-circular window, we calculate the mean trace lengths and two-dimensional (2D) intensity (P21). Additionally, we propose a method to estimate the three-dimensional (3D) intensity (P32), which provides a more comprehensive reflection of the discontinuous characteristics in different spatial orientations. To validate the proposed method, we apply it to the underground drift of the Jiapigou gold mine in Jilin Province to extract the geometric statistical characteristics of discontinuities. The results demonstrate that our method successfully captures the orientation, trace length, and P32 characteristics of four dominant discontinuity groups in the study area. This approach proves to be an effective technique for utilizing 3D laser scanning to obtain accurate discontinuity characteristics of rock mass.

Three-dimensional bound states of cylindrical quantum heterostructures with position-dependent mass carriers

We present a comprehensive spectral analysis of cylindrical quantum heterostructures by considering effective electronic carriers with position-dependent mass for five different kinetic-operator orderings. We obtain the bound energy eigenstates of particles in a three-dimensional cylindrical nanowire under a confining hyperbolic potential with both open and closed boundary conditions in the radial and the axial directions. In the present model we consider carriers with continuous mass distributions within the dot with abrupt mass discontinuities at the barriers, moving in a quantum dot that connects different substances. Continuity of mass and potential at the interfaces with the external layers result as a particular case. Our approach is mostly analytical and allows a precise comparison among von Roos ordering classes.

A computationally efficient approach to automatically extract rock mass discontinuities from 3D point cloud data

Geometric characterization of discontinuity planes in rock masses is an essential practice in rock engineering. Analysis of 3D point cloud data of exposed rock surfaces acquired by remote sensing techniques is becoming widespread due to its benefits such as quality and quantity of the data. In this study, we propose a computationally efficient workflow to extract planar discontinuities from point cloud data automatically. The proposed workflow includes voxel-grid downsampling as a preprocessing step to smooth the point cloud, forming a covariance matrix and applying singular value decomposition to estimate normal vectors, primary clustering to assign the normal vectors to a cluster, secondary clustering to separate individual discontinuity planes in each set, and plane fitting using RANSAC to extract the orientation and location of each discontinuity plane. The proposed workflow's ability to accurately extract discontinuities and calculate their orientations in a computationally efficient procedure was demonstrated through the analysis of two case studies of rock face point clouds.

Reconciling absence of vDVZ discontinuity with absence of ghosts in nonlocal linearized gravity

The modern massive gravity theories resolve a historical tension between the absence of the so called vDVZ mass discontinuity and the absence of ghosts via a fine tuned gravitational potential and a sophisticated screening mechanism. Those theories have originated the modern covariant bimetric models which are local, ghost free and cosmologically viable apparently, they contain a massive plus a massless graviton in the spectrum. It seems hard to solve the mentioned tension if we do insist in a model with a minimal number of degrees of freedom, with only one massive spin-2 particle in the spectrum, even if we allow nonlocal theories. Here we show that this problem can be circumvented in linearized nonlocal theories by the introduction of exponential terms with infinite derivatives. The model admits non linear completions via nonlocal quadratic terms in curvatures. We also investigate the role of the exponential factors in linearized models where the graviton remains massless and a mass scale is introduced via nonlocal terms, they are also ghost free and approach the Einstein–Hilbert theory as we go much above the introduced mass scale.

A non-contact measurement method for rock mass discontinuity orientations by smartphone

A non-contact measurement method for rock mass discontinuity orientations by smartphone

A Laboratory for the Integration of Geomatic and Geomechanical Data: The Rock Pinnacle “Campanile di Val Montanaia”

This work describes a procedure for building a high-quality 3D model of a rocky pinnacle in the Dolomites, Italy, using Structure from Motion (SfM) techniques. The pinnacle, known as “Campanile di Val Montanaia”, is challenging to survey due to its high elevation and sub-vertical cliffs. The construction of the 3D model is the first step in a multi-disciplinary approach to characterize the rock mass and understand its behavior and evolution. This paper discusses the surveying operations, which involved climbing the pinnacle to collect Ground Control Points (GCPs) and using a UAV to capture aerial imagery. The photographs were processed using SfM software to generate point clouds, mesh, and texture, which were then used for rock mass discontinuity mapping. The study compares models of different qualities and point densities to determine the optimal trade-off between processing time and accuracy in terms of discontinuity mapping. The results show that higher quality models allow for more detailed mapping of discontinuities, with some drawbacks due to noise in the case of the densest solution (e.g., increase in frequency of outliers across the point cloud). These pros and cons are also discussed in relation to the computational cost necessary to build the models. The study also examines the limitations and challenges of performing discontinuity mapping in the different models, including subjectivity in interpretation. A further element of interest is the publication of a high-quality 3D georeferenced model of the “Campanile di Val Montanaia” to be used for several potential further applications, such as stability analyses and numerical modeling.