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15 pages, 6629 KiB  
Article
The Contribution of Carbonaceous Material to Gold Mineralization in the Huangjindong Deposit, Central Jiangnan Orogen, China
by Yueqiang Zhou, Zhilin Wen, Yongjun Liu, Jun Wu, Baoliang Huang, Hengcheng He, Yuxiang Luo, Peng Fan, Xiang Wang, Xiaojun Liu, Teng Deng, Ming Zhong, Shengwei Zhang and Mei Xiao
Minerals 2024, 14(10), 1042; https://doi.org/10.3390/min14101042 (registering DOI) - 17 Oct 2024
Abstract
The Huangjindong gold deposit in northeastern Hunan is one of the most representative gold deposits in the Jiangnan Orogenic Belt. The orebodies are mainly hosted in the Neoproterozoic Lengjiaxi Group, which comprises carbonaceous slates. Abundant carbonaceous material (CM) can be found in the [...] Read more.
The Huangjindong gold deposit in northeastern Hunan is one of the most representative gold deposits in the Jiangnan Orogenic Belt. The orebodies are mainly hosted in the Neoproterozoic Lengjiaxi Group, which comprises carbonaceous slates. Abundant carbonaceous material (CM) can be found in the host rocks and ore-bearing quartz veins, but its geological characteristics and genesis, as well as its association with gold mineralization, are still unclear. Systematic petrographic observation demonstrated two types of CM in host rocks and ores, i.e., CM1 and CM2. Among them, CM1 is the predominant type and mainly occurs in the layered carbonaceous slates, while CM2 is mostly present in quartz veins and mineralized host rocks. Laser Raman spectroscopic analyses of CM1 were performed at higher temperatures (376–504 °C), and CM2 was generated at similar temperatures (255–435 °C) to gold mineralization. Combined with previous studies, we can conclude that CM1 was produced by Neoproterozoic to early Paleozoic metamorphism before gold mineralization, while CM2 is of hydrothermal origin. Geochemical modeling indicates that CM1 could promote gold precipitation through reduction, as well as facilitate structure deformation and metal absorption as previously proposed. However, hydrothermal CM2 is favorable for gold mineralization because it triggers sulfidation, similar to other Fe-bearing minerals (such as siderite) in the host rocks. Consequently, both types of CM in the Huangjindong deposit are favorable for gold mineralization and carbonaceous slates could be important gold-bearing units for future ore prospecting in the Jiangnan Orogen as well as other places in South China. Full article
(This article belongs to the Special Issue Microanalysis Applied to Mineral Deposits)
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Figure 1

Figure 1
<p>(<b>a</b>) Simplified tectonic map of South China showing the location of the Jiangnan Orogen (Modified after Sun et al., 2012 [<a href="#B22-minerals-14-01042" class="html-bibr">22</a>]); (<b>b</b>) Geological map of eastern Hunan showing the distribution of structures, lithologies, and major intrusions of different ages, and different types of ore deposits (Modified after Mao et al., 1997 [<a href="#B23-minerals-14-01042" class="html-bibr">23</a>]).</p>
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<p>(<b>a</b>) Geological map of the Huangjindong gold deposit and (<b>b</b>) a cross-section showing ore geological features and related host rocks of the deposit (modified from [<a href="#B31-minerals-14-01042" class="html-bibr">31</a>]).</p>
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<p>Photographs of orebodies and host rocks in the field from the Jinshan gold deposit. (<b>a</b>) carbonaceous slate; (<b>b</b>) bleaching and unaltered carbonaceous slate; (<b>c</b>) CM in the quartz-carbonate veins; (<b>d</b>) CM is associated with sulfides.</p>
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<p>Photomicrographs of ore bodies and host rocks in thin sections from the Huangjindong gold deposit. (<b>a</b>) CM, quartz, sericite, and siderite in the carbonaceous slate; (<b>b</b>,<b>c</b>) CM1 is closely associated with arsenopyrite, pyrite, sphalerite, siderite, and rutile; (<b>d</b>) locally occurring CM in quartz–carbonate veins; (<b>e</b>) the schematic section showing the relationship of the veins and CM. Q, quartz; Ser, sericite; Sd, siderite; Rt, rutile; Py, pyrite; Ccp, chalcopyrite; Sp, sphalerite; Gn, galena.</p>
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<p>(<b>a</b>) The quartz (Q1)–carbonate veins; (<b>b</b>) ankerite in the quartz (Q1)–carbonate veins; (<b>c</b>) scheelite-quartz (Q2) vein is crosscut by the arsenopyrite–pyrite–quartz (Q3) vein; (<b>d</b>) CM2 is closely associated with pyrite and arsenopyrite; (<b>e</b>) polysulphides cut through pyrite and arsenopyrite; (<b>f</b>) quartz-calcite veins. Apy, arsenopyrite; Ank, ankerite.</p>
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<p>Mineralization stages and the paragenesis of the Huangjindong gold deposit.</p>
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<p>(<b>a</b>,<b>b</b>) Raman spectra of CM1; (<b>c</b>,<b>d</b>) Raman spectra of CM2.</p>
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<p>(<b>a</b>) Au solubility diagrams in pH-log <span class="html-italic">f</span>O<sub>2</sub>(g) coordinates at 250 °C with a distribution of Au-bearing aqueous species and Fe-bearing minerals at S = 0.005 mol/kg; (<b>b</b>) mineral precipitation and changes of pH, log <span class="html-italic">f</span>O<sub>2</sub>(g) and S concentrations in fluids at 250 °C when reacting with graphite.</p>
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<p>Mineralization model for the Huangjindong gold deposit. CM1 promotes gold precipitation through reduction, while CM2 favors mineralization by triggering sulfidation. Sd, siderite; CM, Carbonaceous matter; Au, native gold.</p>
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16 pages, 2822 KiB  
Article
Physical-Vapor-Deposition-Coated Natural Rocks as Sustainable Cutting Material: First Insights into the Effect of Substrate Integrity on Properties of TiN Thin Film
by Hilke Petersen, Dominic Graf, Nelson Filipe Lopes Dias, Wolfgang Tillmann, Philipp Dan Hendrik Wolters, Benjamin Bergmann and Bernd Breidenstein
Coatings 2024, 14(10), 1333; https://doi.org/10.3390/coatings14101333 (registering DOI) - 17 Oct 2024
Abstract
The most important cutting materials for machining are carbides. Their production requires both tungsten and cobalt; however, these materials are becoming increasingly difficult to obtain and are sometimes mined under ethically questionable conditions. As a result, increasing efforts are being made to expand [...] Read more.
The most important cutting materials for machining are carbides. Their production requires both tungsten and cobalt; however, these materials are becoming increasingly difficult to obtain and are sometimes mined under ethically questionable conditions. As a result, increasing efforts are being made to expand the range of cutting materials. The basic suitability of natural rocks for cutting tools in less demanding processes has already been demonstrated. PVD coating of the natural rocks could improve their performance. The adhesion mechanisms in TiN-coated natural rock samples are discussed below. The TiN thin film is characterized in depth. Full article
(This article belongs to the Special Issue Modern Methods of Shaping the Structure and Properties of Coatings)
17 pages, 1856 KiB  
Article
Experimental Evaluation of Blockage Resistance and Position Caused by Microparticle Migration in Water Injection Wells
by Jifei Yu, Huan Chen, Yanfeng Cao, Min Wen, Xiaopeng Zhai, Xiaotong Zhang, Tongchuan Hao, Jianlin Peng and Weitao Zhu
Processes 2024, 12(10), 2275; https://doi.org/10.3390/pr12102275 - 17 Oct 2024
Abstract
Offshore oil field loose sandstone reservoirs have high permeability. However, during the water injection process, water injection blockage occurs, causing an increase in injection pressure, making it impossible to continue injecting water on site. Current research mainly focuses on the factors causing water [...] Read more.
Offshore oil field loose sandstone reservoirs have high permeability. However, during the water injection process, water injection blockage occurs, causing an increase in injection pressure, making it impossible to continue injecting water on site. Current research mainly focuses on the factors causing water injection blockage, with less attention given to the blockage locations and the pressure increase caused by water injection. There is a lack of research on the change in the law of injection capacity. This paper establishes a simulation experiment for water injection blockage that can accommodate both homogeneous and heterogeneous cores. The experimental core is 1 m long and capable of simulating the blockage conditions in the near-well zone during water injection, thereby analyzing the core blockage position and blockage pressure. The study clarifies the influence of water quality indicators, heterogeneity, and core length on the blockage patterns in reservoirs during water injection. The research findings are as follows: I. The reservoir blockage samples were characterized using scanning electron microscopy (SEM), casting thin sections, and X-ray diffraction (XRD) analysis. The results indicate that the main factors causing blockage are clay, silt, and fine particulate suspensions, with the fine particles mainly consisting of hydrated silicates and alkali metal oxides. The primary cause of blockage in loose sandstone is identified as the mechanism of migration and accumulation of clay, fine rock particles, and suspended matter in the injected water. II. By monitoring pressure and permeability changes in the core flooding experiments, the impact of reservoir heterogeneity on water injection capacity was evaluated. The evaluation results show that the blockage locations and lengths in heterogeneous cores are twice those in homogeneous cores. III. For heterogeneous reservoirs, if the initial permeability at the inlet is lower than in other segments of the core, significant blockage resistance occurs, with the final resistance being 1.27 times that of homogeneous cores. If the initial permeability at the inlet is higher than in other parts, the final blockage resistance is close to that of homogeneous cores. This study provides theoretical support for the analysis of blockage locations and pressures in loose sandstone water injection and offers technical support for the design of unplugging ranges and pressures after blockage in heterogeneous formations. At the same time, it provides a theoretical basis for selecting the direction of acidizing after blockage occurs in loose sandstone. Full article
(This article belongs to the Section Energy Systems)
22 pages, 2213 KiB  
Article
Mechanical Properties and DEM-Based Simulation of Double-Fractured Sandstone under Cyclic Loading and Unloading
by Lichen Sun, Peijie Lou, Cheng Pan and Penghui Ji
Sustainability 2024, 16(20), 9000; https://doi.org/10.3390/su16209000 - 17 Oct 2024
Abstract
In response to the challenges posed by long-term cyclic loading and unloading in underground rock engineering, this study systematically investigates the macro- and meso-mechanical response mechanisms of fractured rock masses under cyclic loading conditions. We performed graded cyclic loading–unloading tests on parallel double-fractured [...] Read more.
In response to the challenges posed by long-term cyclic loading and unloading in underground rock engineering, this study systematically investigates the macro- and meso-mechanical response mechanisms of fractured rock masses under cyclic loading conditions. We performed graded cyclic loading–unloading tests on parallel double-fractured sandstone samples with varying spatial distribution configurations. These tests were integrated with digital image correlation (DIC) technology, fractal dimension analysis, and discrete element method (DEM) numerical simulations to analyze the mechanical properties, deformation characteristics, crack propagation features, and meso-fracture mechanisms of the fractured rock masses. The findings indicate that the diverse spatial distribution characteristics of the double fractures exert a significant influence on the loading–unloading processes, surface deformation fields, and fracture states of the rock. Cyclic loading leads to an increase in the fractal dimension of the fractured samples, resulting in more intricate and chaotic crack propagation patterns. Furthermore, DEM simulations reveal the impact of fracture spatial configurations on the force chain distribution within the rock bridges. The equivalent stress nephogram effectively represents the stress field distribution. This offers valuable insights for predicting meso-fracture trends in rocks. This paper comprehensively integrates both experimental and numerical simulation methodologies to deliver a thorough analysis of the complex mechanical behavior of fractured rock masses under cyclic loading conditions, with direct relevance to engineering applications such as mine excavation and slope stabilization. Full article
(This article belongs to the Section Sustainable Engineering and Science)
19 pages, 3703 KiB  
Review
Application, Progress, and Trend of Thickened Acid Fracturing in Carbonate Rock Reservoir Development
by Yu Sui, Guangsheng Cao, Yu Tian, Tianyue Guo, Zhongmin Xiao and Liming Yao
Processes 2024, 12(10), 2269; https://doi.org/10.3390/pr12102269 - 17 Oct 2024
Abstract
The efficient development of carbonate rock reservoirs with rich oil and gas resources has become a hot topic and a focal point in the current oil and gas industry. The development of carbonate rock oil and gas reservoirs differs from that of sandstone [...] Read more.
The efficient development of carbonate rock reservoirs with rich oil and gas resources has become a hot topic and a focal point in the current oil and gas industry. The development of carbonate rock oil and gas reservoirs differs from that of sandstone reservoirs. Although gas flooding, water flooding, and chemical flooding have been carried out in recent years, the development is still unsatisfactory, and the on-site application of technologies such as nanoparticles is on the rise. For the future development of acid fracturing technology, accurate reservoir geological description, core printing based on additive manufacturing technology, the development of new acid fracturing techniques, and the research and development of acid fracturing equipment will have great research potential and economic value in the development of carbonate rock oil and gas reservoirs. Under the development background of high-temperature deep reservoirs, this paper comprehensively reviews unconventional acidizing fracturing fluids in carbonate rock oil and gas reservoirs. We introduce the main components, corresponding mechanisms of action, current research achievements, and advantages of promising acid fracturing fluids, including thickened acids. We focus on the application and limitations under harsh conditions of high temperature and high salinity while also focusing on the development of thickened acid fracturing technology. The thickening agent is the core of a thickened acid solution. Therefore, this article fully reviews the structure, sources, advantages and disadvantages, as well as the current development status of biological, cellulose, and synthetic polymer thickeners. Synthetic polymers, low-molecular-weight polymers, and small-molecular compound crosslinkers provide clues for temperature and salt-resistant thickeners and also promote the development of tight reservoirs. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The proven plus probable recoverable reserves of marine carbonates in the world [<a href="#B10-processes-12-02269" class="html-bibr">10</a>,<a href="#B11-processes-12-02269" class="html-bibr">11</a>,<a href="#B12-processes-12-02269" class="html-bibr">12</a>].</p>
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<p>Acid fracturing diagram.</p>
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<p>Mechanism of low salinity water flooding [<a href="#B31-processes-12-02269" class="html-bibr">31</a>].</p>
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<p>Principle and process of polymer flooding. (<b>a</b>) schematic diagram of polymer flooding process [<a href="#B50-processes-12-02269" class="html-bibr">50</a>]; (<b>b</b>) polymer flooding for enhanced oil recovery; (<b>c</b>) viscous fingering phenomenon in water flooding; and (<b>d</b>) polymer flooding mechanism-improving viscous fingering [<a href="#B51-processes-12-02269" class="html-bibr">51</a>,<a href="#B52-processes-12-02269" class="html-bibr">52</a>].</p>
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<p>Proposed mechanism of wettability alteration induced by cationic surfactant in carbonate rock pores. The circles with tails represent cationic surfactants, while the square with a tail represents initially adsorbed anionic amphiphiles present in the oil phase [<a href="#B55-processes-12-02269" class="html-bibr">55</a>].</p>
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<p>EOR mechanism of nanofluids in porous medium [<a href="#B75-processes-12-02269" class="html-bibr">75</a>].</p>
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<p>Comparison of rock slabs etched with emulsified acid and ordinary hydrochloric acid [<a href="#B84-processes-12-02269" class="html-bibr">84</a>]. (<b>a</b>) Top view of dolomite samples etched with 20% HCl at 160 °C; and (<b>b</b>) top view of dolomite samples etched with 20% emulsified acid at 160 °C.</p>
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<p>VES diverting acid dissolving mode [<a href="#B95-processes-12-02269" class="html-bibr">95</a>].</p>
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<p>Principle of action and rheological curve of crosslinking agent. (<b>a</b>) Multinuclear hydroxyl bridge complex ion; and (<b>b</b>) crosslinked acid rheological curve [<a href="#B97-processes-12-02269" class="html-bibr">97</a>].</p>
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<p>Acid transfer caused by foamed acid [<a href="#B110-processes-12-02269" class="html-bibr">110</a>].</p>
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<p>Acid–rock reaction process.</p>
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20 pages, 14818 KiB  
Article
Control of Seepage Characteristics in Loose Sandstone Heap Leaching with Staged Particle Sieving-Out Method
by Quan Jiang, Mingtao Jia, Yihan Yang and Chuanfei Zhang
Minerals 2024, 14(10), 1039; https://doi.org/10.3390/min14101039 - 17 Oct 2024
Abstract
This paper studies the influence of the staged particle sieving-out method on the seepage characteristics in loose sandstone heap leaching. The staged sieving out of ore sample particles was conducted according to particle size, and ground pressure was applied to them. Subsequently, parameters [...] Read more.
This paper studies the influence of the staged particle sieving-out method on the seepage characteristics in loose sandstone heap leaching. The staged sieving out of ore sample particles was conducted according to particle size, and ground pressure was applied to them. Subsequently, parameters such as the permeability, particle distribution, and pore distribution characteristics of the rock samples were obtained to investigate the influence of the staged particle sieving-out method on the seepage effect of loose sandstone heap leaching. The results indicate that sieving out particles smaller than 0.15 mm can significantly reduce the probability of hole blockage and increase the overall pore size, greatly enhancing permeability. Sieving out particles with sizes between 0.15 mm and 1.2 mm can result in the loss of skeleton particles, reducing the amount of flow channels and thereby decreasing permeability. Sieving out particles larger than 1.2 mm can reduce the overall particle size of rock samples, improve strength and pressure stability, and help maintain permeability. In the surface heap leaching of loose sandstone ore, by sieving out particles smaller than 0.15 mm during deep heap construction and sieving out particles larger than 1.2 mm during mid-level heap construction, and by using vat leaching for sieved-out particles, the seepage effect of the ore heap can be significantly optimized, and complete utilization of resources can be ensured. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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Figure 1

Figure 1
<p>Typical surface heap leaching method and stress analysis of ore heap. (<b>a</b>) Typical structure of a heap leaching field; (<b>b</b>) Stress condition of shallow particles; (<b>c</b>) Stress condition of medium-deep particles; (<b>d</b>) Stress condition of deep particles.</p>
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<p>(<b>a</b>) Particle distribution and (<b>b</b>) pore distribution characteristic curves of the original samples.</p>
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<p>Sample preparation. (<b>a</b>) particle size distribution (<b>b</b>) finished samples.</p>
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<p>Samples after pressurization treatment.</p>
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<p>Depth–permeability relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Particle distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Pore distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Free particle distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Depth–free particle proportion relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Effective seepage pore distribution characteristics curve. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Depth–effective seepage pore proportion relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Relationships of (<b>a</b>) free particle proportion–permeability and (<b>b</b>) effective seepage pore proportion–permeability.</p>
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<p>(<b>a</b>–<b>f</b>) Particle distribution difference curve of Group A−F; (<b>g</b>–<b>l</b>) cumulative particle distribution difference curve of Group A−F.</p>
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<p>(<b>a</b>–<b>f</b>) Pore distribution difference curve of Group A−F; (<b>g</b>–<b>l</b>) cumulative pore distribution difference curve of Group A−F.</p>
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<p>Depth–effective seepage pore proportion/total porosity relationship. (<b>a</b>) Group A; (<b>b</b>) Group B; (<b>c</b>) Group C; (<b>d</b>) Group D; (<b>e</b>) Group E; (<b>f</b>) Group F.</p>
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<p>Permeability of various rock samples at different depths.</p>
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<p>B3–A3 and F2–A2 (<b>a</b>) particle difference distribution curve, (<b>b</b>) cumulative particle difference curve, (<b>c</b>) pore difference distribution curve, (<b>d</b>) cumulative pore difference curve.</p>
Full article ">
28 pages, 55964 KiB  
Article
Shear Mechanical Behaviours and Size Effect of Band–Bedrock Interface: Discrete Element Method Simulation Insights
by Hao Wang, Xueyan Guo, Xinrong Liu, Xiaohan Zhou and Bin Xu
Appl. Sci. 2024, 14(20), 9481; https://doi.org/10.3390/app14209481 - 17 Oct 2024
Abstract
The shear band is a prominent feature within the Banbiyan hazardous rock mass located in the Wushan section of the Three Gorges Reservoir area. This band constitutes a latent risk, as the potential for the rock mass to slide along the region threatens [...] Read more.
The shear band is a prominent feature within the Banbiyan hazardous rock mass located in the Wushan section of the Three Gorges Reservoir area. This band constitutes a latent risk, as the potential for the rock mass to slide along the region threatens the safety of lives and property. Presently, the understanding of the shear mechanisms and the impact of shear band size on the band–bedrock interface is incomplete. In this study, based on band–bedrock shear laboratory tests, DEM simulation is used to investigate the shear-induced coalescence mechanism, stress evolution, and crack-type characteristics of the band–bedrock interface. In addition, the shear mechanical properties of samples considering specimen size, rock step height, and step width are further studied. The results show that the crack initiation and failure crack types observed in the first rock step are predominantly tensile. In contrast, the failure cracks in the remaining rock slabs and steps are primarily characterised by shear mode in addition to other mixed modes. The stress condition experienced by the first step is very near to the position of the applied point load, whereas the stress distribution across the remaining steps shows a more complex state of compressive–tensile stress. The relationship between shear parameters and sample size is best described by a negative exponential function. The representative elementary volume (REV) for shear parameters is suggested to be a sample with a geometric size of 350 mm. Notably, the peak shear strength and shear elastic modulus demonstrate a progressive increase with the rise in rock step height, with the amplifications reaching 91.37% and 115.83%, respectively. However, the residual strength exhibits an initial decline followed by a gradual ascent with increasing rock step height, with the amplitude of reduction and subsequent amplification being 23.73% and 116.94%, respectively. Additionally, a narrower rock step width is found to diminish the shear parameter values, which then tend to stabilise within a certain range as the step width increases. Full article
(This article belongs to the Special Issue Recent Advances in Rock Mass Engineering)
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Figure 1

Figure 1
<p>Geographical location and characteristics of shear band in Banbiyan dangerous rock mass.</p>
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<p>Field sampling and parameter measurement: (<b>a</b>) Field sampling; (<b>b</b>) Sample processing; (<b>c</b>) Parametric measurement.</p>
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<p>Experimental model and loading methods: (<b>a</b>) Experimental sample design; (<b>b</b>) Experimental loading methods.</p>
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<p>Numerical model establishment and loading methods: (<b>a</b>) Model establishment; (<b>b</b>) Loading methods.</p>
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<p>Parameter calibration results comparison: (<b>a</b>) Uniaxial compression test; (<b>b</b>) Shear test.</p>
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<p>Curve characteristics and failure modes of sample “L” and “S”: (<b>a</b>) Shear stress–shear displacement curves; (<b>b</b>) Normal displacement–shear displacement curves; (<b>c</b>) Interface failure; (<b>d</b>) Failure mode comparison.</p>
Full article ">Figure 6 Cont.
<p>Curve characteristics and failure modes of sample “L” and “S”: (<b>a</b>) Shear stress–shear displacement curves; (<b>b</b>) Normal displacement–shear displacement curves; (<b>c</b>) Interface failure; (<b>d</b>) Failure mode comparison.</p>
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<p>Failure process and crack evolution of sample under 2 MPa normal stress (Points A to H are different state points in the whole failure process).</p>
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<p>Failure process and crack evolution of sample under 2 MPa normal stress (Points A to H are different state points in the whole failure process).</p>
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<p>Schematics of different crack types (modified from reference [<a href="#B56-applsci-14-09481" class="html-bibr">56</a>]).</p>
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<p>Displacement field and crack type of sample “S-2” during failure process.</p>
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<p>Arrangement of measurement circles.</p>
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<p>Maximum and minimum stress evolution of sample “S-2” during failure process: (<b>a</b>) Point B; (<b>b</b>) Point C; (<b>c</b>) Point D; (<b>d</b>) Point F; (<b>e</b>) Point H.</p>
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<p>Maximum and minimum stress evolution of sample “S-2” during failure process: (<b>a</b>) Point B; (<b>b</b>) Point C; (<b>c</b>) Point D; (<b>d</b>) Point F; (<b>e</b>) Point H.</p>
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<p>Maximum and minimum stress evolution of sample “S-2” during failure process: (<b>a</b>) Point B; (<b>b</b>) Point C; (<b>c</b>) Point D; (<b>d</b>) Point F; (<b>e</b>) Point H.</p>
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<p>Size effect on stress–displacement curves and failure modes: (<b>a</b>) Curve 1 MPa; (<b>b</b>) Curve 2 MPa; (<b>c</b>) Curve 4 MPa; (<b>d</b>) Failure mode 1 MPa; (<b>e</b>) Failure mode 2 MPa; (<b>f</b>) Failure mode 4 MPa.</p>
Full article ">Figure 12 Cont.
<p>Size effect on stress–displacement curves and failure modes: (<b>a</b>) Curve 1 MPa; (<b>b</b>) Curve 2 MPa; (<b>c</b>) Curve 4 MPa; (<b>d</b>) Failure mode 1 MPa; (<b>e</b>) Failure mode 2 MPa; (<b>f</b>) Failure mode 4 MPa.</p>
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<p>Size effect on shear mechanical parameters: (<b>a</b>) 1 MPa; (<b>b</b>) 2 MPa; (<b>c</b>) 4 MPa.</p>
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<p>Effect of step height on sample shear characteristics with geometry size 200 mm: (<b>a</b>) Three typical shear–displacement curves; (<b>b</b>) Three typical failure modes; (<b>c</b>) Shear parameters.</p>
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<p>Effect of step height on sample shear characteristics with geometry size 200 mm: (<b>a</b>) Three typical shear–displacement curves; (<b>b</b>) Three typical failure modes; (<b>c</b>) Shear parameters.</p>
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<p>Effect of step width on sample shear characteristics with geometry size 200 mm: (<b>a</b>) Three typical failure modes; (<b>b</b>) Shear–displacement curves; (<b>c</b>) Shear parameters.</p>
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<p>Effect of step width on sample shear characteristics with geometry size 200 mm: (<b>a</b>) Three typical failure modes; (<b>b</b>) Shear–displacement curves; (<b>c</b>) Shear parameters.</p>
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27 pages, 14949 KiB  
Article
Experimental Study on Strength and Deformation Moduli of Columnar Jointed Rock Mass—Uniaxial Compression as an Example
by Zhenbo Xu, Zhende Zhu, Chao Jiang and Xiaobin Hu
Symmetry 2024, 16(10), 1380; https://doi.org/10.3390/sym16101380 - 17 Oct 2024
Viewed by 218
Abstract
The irregular joint network unique to columnar joints separates the rock mass into several irregular polygonal prisms. Similar physical model specimens of columnar jointed rock mass (CJRM) were fabricated using a rock-like material. The effect of the irregularity of the joint network was [...] Read more.
The irregular joint network unique to columnar joints separates the rock mass into several irregular polygonal prisms. Similar physical model specimens of columnar jointed rock mass (CJRM) were fabricated using a rock-like material. The effect of the irregularity of the joint network was considered in the horizontal plane, and the effect of the dip angle of the joint network was considered in the vertical plane. The strength and deformation moduli of the specimen were investigated using uniaxial compression tests. A total of four failure modes of regular columnar jointed rock mass (RCJRM) and irregular columnar jointed rock mass (ICJRM) were identified through the tests. The peak stress of the irregular columnar jointed rock mass specimen is reduced by 56.65%. The strength and deformation moduli of RCJRM were greater than those of ICJRM, while the anisotropic characteristics of ICJRM were stronger. The failure mode of CJRM was determined by the dip angle. With the increase in the dip angle, the strength and deformation moduli of irregular columnar jointed rock mass are a symmetrical “V” type distribution, 45° corresponds to the minimum strength, and 30° obtains the minimum deformation modulus. With the increase in the irregularity coefficient, the strength and deformation moduli of CJRM decreased first and then increased gradually. When the irregularity coefficient is 0.1, the linear deformation modulus reaches the minimum value. When the irregularity coefficient is 0.7, the median deformation modulus reaches the minimum value. The fitting function proposed in the form of the cosine function managed to predict the strength value of CJRM and showed the strength of the anisotropic characteristics caused by the change in the dip angle. Compared with the existing physical model test results, it is determined that the strength of the specimen is positively correlated with the addition amount of rock-like material and the loading rate, and negatively correlated with the water consumption. Full article
(This article belongs to the Section Engineering and Materials)
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<p>Pictures of CJRM.</p>
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<p>Irregular polygon Voronoi diagrams.</p>
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<p>Normalized area and side length distribution of polygons.</p>
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<p>Specimen fabrication process.</p>
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<p>ICJRM specimens with different joint dip angles.</p>
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<p>Uniaxial compression test system and specimen loading diagram.</p>
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<p>Stress–strain curves of CJRM specimens.</p>
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<p>Stress–strain curves of CJRM specimens.</p>
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<p>The influence of the irregularity coefficient and the inclination angle on peak stress.</p>
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<p>Failure modes of RCJRM specimens with different dip angles.</p>
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<p>Failure modes of ICJRM specimens with different dip angles.</p>
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<p>Effect of the irregularity coefficient on the peak stress.</p>
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<p>Schematic diagram of the value-taking methods for the specimen deformation modulus.</p>
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<p>Effect of the dip angle on the deformation modulus.</p>
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<p>Effect of the irregularity coefficient on the deformation modulus.</p>
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<p>Specimen cracking evolution.</p>
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<p>Effect of the irregularity coefficient on the anisotropy ratio coefficient.</p>
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<p>Effect of the irregularity coefficient on the area of the anisotropy region. (<b>a</b>) Area of the anisotropy region when the irregularity coefficient was 0.1 (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mn>0.1</mn> </mrow> </msub> </mrow> </semantics></math>); (<b>b</b>) Areas of the anisotropy regions when the irregularity coefficients were 0.3 (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mn>0.3</mn> </mrow> </msub> </mrow> </semantics></math>), 0.5 (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mn>0.5</mn> </mrow> </msub> </mrow> </semantics></math>), and 0.7 (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mn>0.7</mn> </mrow> </msub> </mrow> </semantics></math>).</p>
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<p>Summary of the anisotropy index values. It is compared with the data in the references [<a href="#B11-symmetry-16-01380" class="html-bibr">11</a>,<a href="#B22-symmetry-16-01380" class="html-bibr">22</a>,<a href="#B24-symmetry-16-01380" class="html-bibr">24</a>,<a href="#B34-symmetry-16-01380" class="html-bibr">34</a>,<a href="#B37-symmetry-16-01380" class="html-bibr">37</a>,<a href="#B38-symmetry-16-01380" class="html-bibr">38</a>].</p>
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<p>Peak stress fitting curves.</p>
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<p>Comparison between the fitted values and the test values under the optimum fitting condition.</p>
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<p>MAPE values of the simplified fitting functions.</p>
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<p>Comparison between the fitted values and the test values under the simplified fitting condition.</p>
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<p>Comparison between the fitted values obtained by two fitting methods and test values.</p>
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22 pages, 9243 KiB  
Article
Physical and Numerical Modeling of a Flow Control Layer Made with a Sludge and Slag Mixture for Use in Waste Rock Pile Reclamation
by Nelcy Carolina Otalora Vasquez, Abdelkabir Maqsoud and Tikou Belem
Mining 2024, 4(4), 841-862; https://doi.org/10.3390/mining4040047 - 16 Oct 2024
Viewed by 183
Abstract
The reclamation of waste rock piles (WRPs) is complex, requiring adaptation of existing mine site reclamation techniques. An alternative approach has been developed for waste rock piles reclamation which involves installing finer materials on the top of waste rock piles. These finer layers [...] Read more.
The reclamation of waste rock piles (WRPs) is complex, requiring adaptation of existing mine site reclamation techniques. An alternative approach has been developed for waste rock piles reclamation which involves installing finer materials on the top of waste rock piles. These finer layers (flow control layers—FCLs) redirect water flowing inside the pile toward its slope and limits water infiltration into reactive waste rocks. In the context of sustainable development, a mixture material made with sludge and slag can be used as an FCL in the reclamation of a waste rock pile. To assess the effectiveness of this material, a physical model was used and instrumented with sensors for monitoring volumetric water content and suction and equipped with the following components: (1) a rain simulator; and (2) drains that allow the recovery of water that infiltrates through the system. The physical model was tested with various cover layer thicknesses, inclinations, and precipitation rates. Investigation results showed that the water infiltration across the system was very low, leading to the conclusion that the sludge and slug mixture performed well as a flow control layer in the reclamation of waste rock piles. Full article
(This article belongs to the Topic Mining Innovation)
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<p>Quémont 2 mine site location (<a href="https://mapamundi.online" target="_blank">https://mapamundi.online</a> maps images, accessed on 11 July 2024).</p>
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<p>Particle size distribution of materials.</p>
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<p>Measured and fitted water retention curves of the sludge and slag mixture.</p>
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<p>Experimental setup: (<b>a</b>) laboratory physical model; (<b>b</b>) locations of different devices used for volumetric water content (θ), suction (ψ) measurements, and drains used to recover infiltration and runoff.</p>
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<p>Numerical model and location of simulated sensors in SEEP/W.</p>
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<p>Volumetric water content of the gravel and the sludge–slag materials.</p>
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<p>Permeability function of the gravel and the sludge–slag materials.</p>
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<p>Infiltration and runoff rates for different drains and for different slope and thickness scenarios: (<b>a</b>) thickness of 25 cm; (<b>b</b>) thickness of 50 cm; and (<b>c</b>) thickness of 75 cm.</p>
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<p>Infiltration and runoff rates for different slope and thickness scenarios.</p>
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<p>Saturation profiles for the scenario with an FCL thickness of 25 cm and a slope of 2.5°.</p>
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<p>Suction profiles for the scenario with an FCL thickness of 25 cm and slope 2.5.</p>
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<p>Saturation profiles for the scenario with an FCL thickness of 50 cm and a slope of 5°.</p>
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<p>Suction profiles for the scenario with an FCL thickness of 50 cm and a slope of 5°.</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 2.5°, a layer thickness of 25 cm, and a period of 720 h (30 days).</p>
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<p>Volumetric water content results at a precipitation rate of 46.8 mm/h, a slope of 2.5°, a layer thickness of 25 cm, and a period of 5 h.</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 5°, a layer thickness of 25 cm, and a period of 720 h (30 days).</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 5°, a layer thickness of 25 cm, and a period of 5 h.</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 2.5°, a layer thickness of 50 cm, and a period of 720 h (30 days).</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 2.5°, a layer thickness of 50 cm, and a period of 5 h.</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 5°, a layer thickness of 50 cm, and a period of 720 h (30 days).</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 5°, a layer thickness of 50 cm, and a period of 5 h.</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 2.5°, a layer thickness of 75 cm, and a period of 720 h (30 days).</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 2.5°, a layer thickness of 75 cm, and a period of 5 h.</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 5°, a layer thickness of 75 cm, and a period of 720 h (30 days).</p>
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<p>Volumetric water content results for a precipitation of 46.8 mm/h, a slope of 5°, a layer thickness of 75 cm, and a period of 5 h.</p>
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<p>Photos showing FCLs at 2.5° and 5° slopes which were not affected by superficial erosion.</p>
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<p>Visible superficial erosion for an FCL with a 10° slope.</p>
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14 pages, 1467 KiB  
Article
Acid Mine Drainage Neutralization by Ultrabasic Rocks: A Chromite Mining Tailings Evaluation Case Study
by Evgenios Kokkinos, Vasiliki Kotsali, Evangelos Tzamos and Anastasios Zouboulis
Sustainability 2024, 16(20), 8967; https://doi.org/10.3390/su16208967 - 16 Oct 2024
Viewed by 273
Abstract
Chromite is formed in nature in ophiolitic layers and ultrabasic rocks through fractional crystallization. The corresponding mining technologies separate the ore from these ultrabasic rocks, which are considered to be tailings for the process but may be valorized in other applications. The need [...] Read more.
Chromite is formed in nature in ophiolitic layers and ultrabasic rocks through fractional crystallization. The corresponding mining technologies separate the ore from these ultrabasic rocks, which are considered to be tailings for the process but may be valorized in other applications. The need to utilize this material is due to the large quantities of its production and the special management required to avoid possible secondary pollution. In the present work, the ultrabasic rocks of chromite mining were applied to acid mine drainage (AMD) neutralization. The aim was to increase the technological maturity of the method and promote circular economy principles and sustainability in the mining sector. Ultrabasic rocks were obtained from a chromite mining facility as reference material. Furthermore, an artificial AMD solution was synthesized and applied, aiming to simulate field conditions. According to the results, the sample was successfully utilized in AMD neutralization (pH 7), achieving rapid rates in the first 30 min and maximum efficiency (liquid to solid ratio equal to 8.3) at 24 h. However, the method presented a drawback since Mg was leached, even though the concentration of other typical metals contained in an AMD solution decreased. Full article
(This article belongs to the Special Issue Sustainable Mining and Circular Economy)
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<p>XRD diagram of the ultrabasic rock obtained from chromite mine.</p>
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<p>ANC diagram of the ultrabasic rock obtained from chromite mine.</p>
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<p>The kinetic study of the neutralization process by applying 1 g of sample at 0.01 M H<sub>2</sub>SO<sub>4</sub>: (<b>a</b>) equilibrium pH and conductivity, and (<b>b</b>) Fe and Mg concentration in the residual liquid phase.</p>
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<p>Neutralization of 0.01 M H<sub>2</sub>SO<sub>4</sub> by applying different amounts of the sample (1–6 g): (<b>a</b>) equilibrium pH and conductivity at 30 min of experimental time, (<b>b</b>) Fe and Mg concentration in the residual liquid phase at 30 min of experimental time, (<b>c</b>) equilibrium pH and conductivity at 24 h of experimental time, and (<b>d</b>) Fe and Mg concentration in the residual liquid phase at 24 h of experimental time.</p>
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<p>Neutralization of artificial AMD solution by applying different amounts of the sample (1–8 g): (<b>a</b>) equilibrium pH and conductivity at 30 min of experimental time, (<b>b</b>) percentage of metals content decrease and increase (refers only to Mg) in the residual liquid phase at 30 min of experimental time, (<b>c</b>) equilibrium pH and conductivity at 24 h of experimental time, and (<b>d</b>) percentage of metals content decrease and increase and increase (refers only to Mg) in the residual liquid phase at 24 h of experimental time.</p>
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<p>XRD diagrams of the used ultrabasic rock were obtained after 30 min and 24 h of neutralizing time.</p>
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31 pages, 114861 KiB  
Article
Multitemporal Monitoring of Rocky Walls Using Robotic Total Station Surveying and Persistent Scatterer Interferometry
by Luisa Beltramone, Andrea Rindinella, Claudio Vanneschi and Riccardo Salvini
Remote Sens. 2024, 16(20), 3848; https://doi.org/10.3390/rs16203848 - 16 Oct 2024
Viewed by 236
Abstract
Rockfall phenomena are considered highly dangerous due to their rapid evolution and difficult prediction without applying preventive monitoring and mitigation actions. This research investigates a hazardous site in the Municipality of Vecchiano (Province of Pisa, Italy), characterized by vertical rock walls prone to [...] Read more.
Rockfall phenomena are considered highly dangerous due to their rapid evolution and difficult prediction without applying preventive monitoring and mitigation actions. This research investigates a hazardous site in the Municipality of Vecchiano (Province of Pisa, Italy), characterized by vertical rock walls prone to instability due to heavy fracturing and karst phenomena. The presence of anthropical structures and a public road at the bottom of the slopes increases the vulnerability of the site and the site’s risk. To create a comprehensive geological model of the area, Unmanned Aircraft System (UAS) photogrammetric surveys were conducted to create a 3D model useful in photointerpretation. In accessible and safe areas for personnel, engineering–geological surveys were carried out to characterize the rock mass and to define the portion of rock walls to be monitored. Results from nine multitemporal Robotic Total Station (RTS) measurement campaigns show that no monitoring prisms recorded significant displacement trends, both on the horizontal and vertical plane and in differential slope distance. Additionally, satellite Persistent Scatterer Interferometry (PSI) analysis indicates that the slopes were stable over the two years of study. The integration of these analysis techniques has proven to be an efficient solution for assessing slope stability in this specific rockfall-prone area. Full article
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<p>Geological framework of the study site. (<b>A</b>) The site location in Italy; (<b>B</b>) the regional geological framework (Sheet n.273 “Pisa”) modified from [<a href="#B54-remotesensing-16-03848" class="html-bibr">54</a>]; (<b>C</b>) a subset of the geological map n.273 “Pisa” [<a href="#B54-remotesensing-16-03848" class="html-bibr">54</a>]; the red star in (<b>C</b>) indicates the precise location of the study area.</p>
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<p>Overall methodology flowchart.</p>
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<p>Stages of the GNSS (<b>A</b>) and RTS surveys (<b>B</b>).</p>
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<p>Photos in (<b>A</b>,<b>B</b>) show some examples of outcrops selected for the in situ engineering–geological survey; the yellow dashed lines in (<b>C</b>) indicate the location of scanlines along the slope; the red boxes in (<b>C</b>) show the areas where discontinuity sampling was performed through CloudCompare software (version 2).</p>
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<p>Robotic Total Station (RTS) on the iron plate anchored to a reinforced concrete curb (<b>A</b>); view of the rock walls to be monitored from the RTS position (<b>B</b>); macroprism and microprism utilized for the RTS multitemporal surveys (<b>C</b>).</p>
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<p>Location of RTS base (in yellow) and prisms; green colors indicate the reference prisms utilized to orient the monitoring system; red colors indicate the monitoring prisms periodically measured during the nine surveys.</p>
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<p>Example of error ellipse for the B4 monitoring prism.</p>
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<p>Metallic corner reflectors installed on the top edge above the rocky walls: location of corner reflectors in the study area (<b>A</b>). Photos in <b>CR1</b>, <b>CR2,</b> and <b>CR3</b> show detailed images of the corner reflectors.</p>
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<p>Satellite imagery covering the area of interest (<b>A</b>); satellite imagery spatially corresponding to the same area of interest (<b>B</b>). The yellow square shows the area of interest.</p>
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<p>Perspective view of the georeferenced and scaled 3D point cloud of the rocky walls; the scale bar only applies to (<b>A</b>). Georeferenced orthophotomosaic of the rocky walls and the alluvial plain (<b>B</b>).</p>
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<p>Stereographic projection (Schmidt equal-area method—lower hemisphere) of data collected during the in situ engineering–geological survey.</p>
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<p>Stereographic projection (Schmidt equal-area method—lower hemisphere) of data interpreted on the 3D point cloud.</p>
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<p>Slopes considered for the application of the SMR method and the following statistical kinematic stability analysis (<a href="#sec4dot4-remotesensing-16-03848" class="html-sec">Section 4.4</a>). The stereographic projections (Wulff equal-angle method—lower hemisphere) show an example of the executed kinematic analysis (ex., wedge sliding).</p>
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<p>Planimetric representation of multitemporal monitoring results (monitoring prisms from B1 to B15). The error ellipses for the monitoring prisms are indicated in orange. The points, differentiated by color, indicate the 9 multitemporal surveys.</p>
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<p>Planimetric representation of multitemporal monitoring results (monitoring prisms from B16 to B30). The error ellipses for the monitoring prisms are indicated in orange. The points, differentiated by color, indicate the 9 multitemporal surveys.</p>
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<p>Differential slope distance (<b>A</b>) and elevation displacement (<b>B</b>) of each prism measured in all the RTS surveys. The uncertainty thresholds for each prism are indicated by the red vertical bars.</p>
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<p>Differential slope distance (<b>A</b>) and elevation displacement (<b>B</b>) of each prism as computed with respect to R4. The uncertainty thresholds for each prism are indicated by the red vertical bars.</p>
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<p>Results of the PSI analysis in terms of LOS velocities (mm/yr) for the Sentinel-1A (<b>A</b>) and Sentinel-1B data (<b>B</b>). The yellow squares represent the position of the artificial corner reflectors installed at the top of the rocky slopes in this work. The blue triangle indicates the building where the RTS is installed.</p>
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<p>PSs identified by the regional LaMMa interferometric service for the study area. The red circle identifies the point FV6XKKY located near the RTS. The diagram at the bottom of the map shows the trend of this PS LOS velocity (mm/yr) considering the same interval of the RTS monitoring time span. The light blue ellipses indicate the acquisition dates of the 7th and 8th RTS surveys.</p>
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<p>Differential slope distance (<b>A</b>) and elevation displacement (<b>B</b>) of each prism as measured during the survey carried out on 4 March 2024.</p>
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20 pages, 27208 KiB  
Article
Optimization of Organic Rankine Cycle for Hot Dry Rock Power System: A Stackelberg Game Approach
by Zhehao Hu, Wenbin Wu and Yang Si
Energies 2024, 17(20), 5151; https://doi.org/10.3390/en17205151 - 16 Oct 2024
Viewed by 250
Abstract
Due to its simple structure and stable operation, the Organic Rankine Cycle (ORC) has gained significant attention as a primary solution for low-grade thermal power generation. However, the economic challenges associated with development difficulties in hot dry rock (HDR) geothermal power systems have [...] Read more.
Due to its simple structure and stable operation, the Organic Rankine Cycle (ORC) has gained significant attention as a primary solution for low-grade thermal power generation. However, the economic challenges associated with development difficulties in hot dry rock (HDR) geothermal power systems have necessitated a better balance between performance and cost effectiveness within ORC systems. This paper establishes a game pattern of the Organic Rankine Cycle with performance as the master layer and economy as the slave layer, based on the Stackelberg game theory. The optimal working fluid for the ORC is identified as R600. At the R600 mass flow rate of 50 kg/s, the net system cycle work is 4186 kW, the generation efficiency is 14.52%, and the levelized cost of energy is 0.0176 USD/kWh. The research establishes an optimization method for the Organic Rankine Cycle based on the Stackelberg game framework, where the network of the system is the primary optimization objective, and the heat transfer areas of the evaporator and condenser serve as the secondary optimization objective. An iterative solving method is utilized to achieve equilibrium between the performance and economy of the ORC system. The proposed method is validated through a case study utilizing hot dry rock data from Qinghai Gonghe, allowing for a thorough analysis of the working fluid and system parameters. The findings indicate that the proposed approach effectively balances ORC performance with economic considerations, thereby enhancing the overall revenue of the HDR power system. Full article
(This article belongs to the Special Issue Big Data Analysis and Application in Power System)
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<p>ORC system flowchart.</p>
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<p>Schematic diagram of Stackelberg game pattern for ORC system optimization.</p>
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<p>Shell and tube heat exchanger geometry.</p>
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<p>Schematic diagram of heat exchange process of evaporator.</p>
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<p>Schematic diagram of tube bundle arrangement.</p>
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<p>Schematic diagram of condenser heat exchange process.</p>
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<p>ORC system optimization Stackelberg game approach.</p>
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<p>Optimal network of organic working fluids.</p>
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<p>Minimum heat transfer area per kW for organic working fluids.</p>
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<p>Levelized cost of energy for organic working fluids.</p>
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<p>Relationship between tube bundle arrangement and heat transfer area.</p>
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16 pages, 1099 KiB  
Article
Geophysical Monitoring Technologies for the Entire Life Cycle of CO2 Geological Sequestration
by Chenyang Li and Xiaoli Zhang
Processes 2024, 12(10), 2258; https://doi.org/10.3390/pr12102258 - 16 Oct 2024
Viewed by 325
Abstract
Geophysical monitoring of CO2 geological sequestration represents a critical technology for ensuring the long-term safe storage of CO2 while verifying its characteristics and dynamic changes. Currently, the primary geophysical monitoring methods employed in CO2 geological sequestration include seismic, fiber optic, [...] Read more.
Geophysical monitoring of CO2 geological sequestration represents a critical technology for ensuring the long-term safe storage of CO2 while verifying its characteristics and dynamic changes. Currently, the primary geophysical monitoring methods employed in CO2 geological sequestration include seismic, fiber optic, and logging technologies. Among these methods, seismic monitoring techniques encompass high-resolution P-Cable three-dimensional seismic systems, delayed vertical seismic profiling technology, and four-dimensional distributed acoustic sensing (DAS). These methods are utilized to monitor interlayer strain induced by CO2 injection, thereby indirectly determining the injection volume, distribution range, and potential diffusion pathways of the CO2 plume. In contrast, fiber optic monitoring primarily involves distributed fiber optic sensing (DFOS), which can be further classified into distributed acoustic sensing (DAS) and distributed temperature sensing (DTS). This technology serves to complement seismic monitoring in observing interlayer strain resulting from CO2 injection. The logging techniques utilized for monitoring CO2 geological sequestration include neutron logging methods, such as thermal neutron imaging and pulsed neutron gamma-ray spectroscopy, which are primarily employed to assess the sequestration volume and state of CO2 plumes within a reservoir. Seismic monitoring technology provides a broader monitoring scale (ranging from dozens of meters to kilometers), while logging techniques operate at centimeter to meter scales; however, their results can be significantly affected by the heterogeneity of a reservoir. Full article
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<p>Schematic diagram of a common CO<sub>2</sub> water rock reaction device. (<b>a</b>) Modified by Wang et al., 2016 [<a href="#B12-processes-12-02258" class="html-bibr">12</a>]. (<b>b</b>) According to Cui et al.’s revision, 2024 [<a href="#B14-processes-12-02258" class="html-bibr">14</a>]. (<b>c</b>) Modified by Liu et al., 2019 [<a href="#B15-processes-12-02258" class="html-bibr">15</a>].</p>
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<p>Common wellbore integrity laboratory monitoring device (modified by Mamoudou et al., 2024 [<a href="#B24-processes-12-02258" class="html-bibr">24</a>]).</p>
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<p>Whole life cycle geophysical monitoring process of CO<sub>2</sub> geological storage.</p>
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23 pages, 13906 KiB  
Article
FLAC3D Simulation of Caving Mechanism and Strata Fracture Response in Underground Mining
by Mahdi Saadat, Mattin Khishvand and Andrew Seccombe
Mining 2024, 4(4), 818-840; https://doi.org/10.3390/mining4040046 - 16 Oct 2024
Viewed by 172
Abstract
This paper presents an innovative numerical approach to simulating the progressive caving of rock mass in the overburden and floor during longwall mining. A modified caving algorithm is incorporated into FLAC3D 9.0, augmented with the IMASS constitutive model, to accurately replicate the fracturing [...] Read more.
This paper presents an innovative numerical approach to simulating the progressive caving of rock mass in the overburden and floor during longwall mining. A modified caving algorithm is incorporated into FLAC3D 9.0, augmented with the IMASS constitutive model, to accurately replicate the fracturing response of various strata. This study aimed to analyze the longwall caving performance, overburden fracturing response, and shield support characteristics to optimize the mining process and enhance safety. The numerical analysis revealed a progressive stress release at the longwall face, attributed to damage in the form of spalling, which was accompanied by a high level of displacement. The fracture process zone above the shield canopy was not significant, indicating the effective performance of the shield in controlling the roof. However, the floor heave highlights the need for the implementation of effective risk and safety measures. Goaf is predicted to form with a longwall advance rate of 25.0–30.0 m, resulting from progressive macroscopic fracturing caused by the development of cracks initiated by bedding plane and rock mass failures. Above the caved zone, an active fracture zone is observed to evolve due to the continuous longwall mining and caving process. Full article
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<p>Lithological sequence and geometry imported into the FLAC3D 9.0 model (section view). SS = sandstone; ST = siltstone; XM = carbonaceous mudstone; XT = carbonaceous siltstone; XS = carbonaceous sandstone; ST/SS = siltstone/sandstone; CO = coal.</p>
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<p>Geometrical details of the shield support created in the FLAC3D 9.0 model (section view).</p>
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<p>A 3D view of the shield support element generated in FLAC3D 9.0 for simulating a longwall support system. The model is assumed to perform in the plane strain condition.</p>
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<p>The cave-in conceptual model. The distribution of maximum principal strain indicates fracturing. The original model can be found in [<a href="#B5-mining-04-00046" class="html-bibr">5</a>,<a href="#B29-mining-04-00046" class="html-bibr">29</a>].</p>
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<p>Pseudocode for the caving simulation methodology used in FLAC3D 9.0.</p>
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<p>The numerical outcomes of the caving algorithm implemented in FLAC3D 9.0. Fracture domain included in the final goaf (<math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msup> </mrow> </semantics></math> of 3.0–5.0% or higher).</p>
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<p>The maximum principal strain (%). The goaf thickness is approximately 20.0–22.0 m. (The strain contours are depicted between 0 and 5% to demonstrate the fracturing process.) A schematic view of shield support is shown in the figure.</p>
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<p>Maximum principal strain (%). Zoomed-in view of the shield front. (The strain contours are depicted between 0 and 5% to demonstrate the fracturing process.) A schematic view of shield support is shown in the figure.</p>
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<p>Displacement response in the shield region. Displacement of the shield front, roof, and floor are monitored, as shown in the model. A schematic view of shield support is shown in the figure.</p>
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<p>Vertical and horizontal displacement of the shield front. A schematic view of shield support is shown in the figure.</p>
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<p>Vertical and horizontal displacement of the shield front. A schematic view of shield support is shown in the figure.</p>
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<p>Damage response of the caved region: 0% represents no damage and 100% represents complete failure. Any value between 0 and 100% demonstrates the fracturing response. A schematic view of shield support is shown in the figure.</p>
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<p>Plasticity state of the caved region. shear-n: failure in shear now; shear-p: failure in shear in the past; tension-p: failure in tension in the past. A schematic view of shield support is shown in the figure.</p>
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<p>Damage response of the front shield: 0% represents no damage and 100% represents complete failure. Any value between 0 and 100% demonstrates the fracturing response. A schematic view of shield support is shown in the figure.</p>
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<p>Plasticity state of the shield front. shear-n: failure in shear now; shear-p: failure in shear in the past; tension-p: failure in tension in the past. A schematic view of shield support is shown in the figure.</p>
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<p>Damage response of the model plotted with corresponding lithological units. A schematic view of shield support is shown in the figure.</p>
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<p>Maximum principal stress (σ1) contours. A schematic view of shield support is shown in the figure.</p>
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<p>Minimum principal stress (σ3) contours. A schematic view of shield support is shown in the figure.</p>
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<p>Periodic weighting event potential predicted by the numerical model. A schematic view of shield support is shown in the figure.</p>
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12 pages, 2559 KiB  
Article
The Stability and Failure of Deep Underground Structures at Potash Mining Deposits
by Yiqiang Zhang, Siarhei Lapatsin, Michael Zhuravkov, Guangbin Yu and Ivan Karpovich
Appl. Sci. 2024, 14(20), 9434; https://doi.org/10.3390/app14209434 - 16 Oct 2024
Viewed by 213
Abstract
The article describes the peculiarities of strength and stability evaluation for deep geotechnical structures located in salt rock masses at great depths. A number of numerical studies are presented for the deep mining excavations of various cross-sections. The numerical simulations are conducted using [...] Read more.
The article describes the peculiarities of strength and stability evaluation for deep geotechnical structures located in salt rock masses at great depths. A number of numerical studies are presented for the deep mining excavations of various cross-sections. The numerical simulations are conducted using a specific coupled algorithm of the finite element method (FEM) and distinct element method (DEM), which allows not only the prediction of dangerous zones in the undermined rock mass but also to simulation of the block fracture of the rock mass directly. Potential critical zones in the rock mass are established using an original complex limit state criterion for rock masses and FEM simulation results. Mentioned original criterion is a specific multicriterial method, which considers potential tensile, compressive and shear failure as well as crack propagation. To define the block-structure formulation in the rock mass it is proposed to use the Lade criterion in the complex limit state zones. Furthermore, block-structured rock mass behavior is simulated using DEM to predict its block-like fracture. The results of numerical studies clearly show that the mechanical behavior of potash salt rock masses significantly differ at moderate and great mining depths. Namely, the volume of the limit state zones nonlinearly increases with the increase in the mining depths up to double the size of the excavation cross-section. However, the exact amount of potentially failed rock mass has to be established using the direct DEM simulation in the limit state zones. Full article
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Figure 1

Figure 1
<p>Typical cross-sections of mining excavations for potash mining deposits. (<b>a</b>) Filleted square cross-section, (<b>b</b>) Arched cross-section.</p>
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<p>Distributions of the Nadai–Lode coefficient in the vicinity of mining excavations of different cross-sections at moderate and significant mining depths. Red color—zones of generalized compression; green color—zones of generalized shear; and blue color—zones of generalized tension.</p>
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<p>Limit states of the rock mass in the vicinity of mining excavations of different cross-sections at moderate and great mining depths according to complex limit state criterion (3). Red color—limit state zones; black lines—pressure vaults.</p>
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<p>Limit states of the rock mass in the vicinity of mining excavations of different cross-sections at great mining depth (H = 1200 m) according to complex limit state criterion (3). Red color—limit state zones.</p>
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<p>Crack propagation in the vicinity of the considered mining excavations according to the Lade criterion (7) at a great depth of 1200 m. Red color—crack propagation areas.</p>
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<p>Crack propagation in the vicinity of the considered mining excavations according to the Griffith criterion (4) at a great depth of 1200 m. Red color—crack propagation areas.</p>
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<p>Block structure formulation at the depths of 1200 m according to the Lade criterion (7).</p>
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<p>Block structure formulation at the depths of 1200 m according to the Griffith criterion.</p>
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<p>The results of the DEM simulation for the mining excavations at the depths of 1200 m.</p>
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