[go: up one dir, main page]

 
 

Topic Editors

School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Prof. Dr. Xinmin Wang
School of Resources and Safety Engineering, Central South University, Changsha 410083, China

New Advances in Mining Technology

Abstract submission deadline
closed (20 July 2024)
Manuscript submission deadline
20 September 2024
Viewed by
7507

Topic Information

Dear Colleagues,

The mining industry plays a vital role in the global economy. Today, more than 92% of the world's primary energy, 80% of industrial raw materials, and 70% of agricultural production means are derived from mineral resources. This Topic aims to highlight the current state of knowledge on the new advancements in mining technology, including case studies of specific mining projects and the development of new technologies and practices. This Topic will cover a range of topics related to mining technology including, but not limited to, new mining equipment, mining materials, and safety technologies, as well as social and economic impacts. By highlighting the development of new mining technologies and practices, this Topic hopes to contribute to a more sustainable and responsible mining industry.

Potential topics include, but are not limited to, the following:

  • Automated and intelligent mining equipment;
  • Mining technology of complex and difficult mining body;
  • New low-cost mineral materials;
  • New technology of mining safety management;
  • Mining waste management and remediation;
  • Social and economic impacts of mining industry;
  • Sustainable mining practices and environmental regulations;
  • Case studies of successful modern green mines.

Dr. Shuai Li
Prof. Dr. Xinmin Wang
Topic Editors

Keywords

  • intelligent mining equipment
  • new mining technology
  • new mining materials, mining safety technology
  • mining waste management
  • sustainable mining practices
  • modern green mines

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.5 5.3 2011 17.8 Days CHF 2400 Submit
Energies
energies
3.0 6.2 2008 17.5 Days CHF 2600 Submit
Materials
materials
3.1 5.8 2008 15.5 Days CHF 2600 Submit
Minerals
minerals
2.2 4.1 2011 18 Days CHF 2400 Submit
Processes
processes
2.8 5.1 2013 14.4 Days CHF 2400 Submit
Resources
resources
3.6 7.2 2012 33.4 Days CHF 1600 Submit

Preprints.org is a multidiscipline platform providing preprint service that is dedicated to sharing your research from the start and empowering your research journey.

MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication:

  1. Immediately share your ideas ahead of publication and establish your research priority;
  2. Protect your idea from being stolen with this time-stamped preprint article;
  3. Enhance the exposure and impact of your research;
  4. Receive feedback from your peers in advance;
  5. Have it indexed in Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (8 papers)

Order results
Result details
Journals
Select all
Export citation of selected articles as:
19 pages, 11091 KiB  
Article
Failure Characteristics and Cooperative Control Strategies for Gob-Side Entry Driving near an Advancing Working Face: A Case Study
by Wenda Wu, Tianchen Wang, Jianbiao Bai, Jinhu Liu, Xiangyu Wang, Haiyun Xu and Guorui Feng
Processes 2024, 12(7), 1398; https://doi.org/10.3390/pr12071398 - 4 Jul 2024
Viewed by 411
Abstract
Gob-side entry driving near an advancing working face can improve the recovery rate of coal resources and keep the balance between mining and development. However, the large displacement of the gob-side entry caused by the mining dynamics of abutment pressure challenges the safety [...] Read more.
Gob-side entry driving near an advancing working face can improve the recovery rate of coal resources and keep the balance between mining and development. However, the large displacement of the gob-side entry caused by the mining dynamics of abutment pressure challenges the safety and processes of coal mining. This article takes the 15102 tailentry of Xizhang Coal Mine in Changzhi City, Shanxi Province, as an example to study the stability of the coal pillar and the failure characteristics of the surrounding rock and proposes cooperative control strategies of surrounding rock stability. Field tests indicated that when the coal pillar width was 15 m, the displacements of the entry floor, roof, coal pillar side, and solid coal side were 1121 mm, 601 mm, 783 mm, and 237 mm, respectively. A meticulously validated numerical model, incorporating a double-yield model for the gob materials and calibrated parameters, was developed to investigate the stress changes and yield zone distribution across the coal pillar with different sizes. The results of the simulation indicate that the influence range of the dynamic abutment pressure caused by mining in the upper section of gob-side entry driving is 30 m ahead and 70 m behind. When the coal pillar width increases from 7 m to 20 m, the internal stress of the coal pillar increases continuously, while the internal stress of the solid coal decreases continuously. It is estimated that the reasonable coal pillar width should be 7 m, which is subjected to a lower load. The cooperative control strategies comprising a narrow coal pillar, hydraulic fracturing roof cutting for pressure relief, and entry dynamic support were proposed and applied in the 15103 tailentry. The final displacements of the floor, roof, coal pillar side, and solid coal side were 66.01%, 62.06%, 61.05%, and 63.30% lower than that of the 15102 tailentry in the same period, respectively, which effectively controlled the stability of surrounding rock. In addition, this finding for the gob-side entry driving near an advancing working face in this study can potentially be applied to other similar projects. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Position of gob-side entry driving near an advancing working face.</p>
Full article ">Figure 2
<p>Mine development plan and lithologic column.</p>
Full article ">Figure 3
<p>Mechanical properties of strata.</p>
Full article ">Figure 4
<p>Entry monitoring points and displacement.</p>
Full article ">Figure 5
<p>Numerical model.</p>
Full article ">Figure 6
<p>Measurement scheme.</p>
Full article ">Figure 7
<p>Comparison of the stress–strain curves between the numerical model and the Salamon model.</p>
Full article ">Figure 8
<p>Vertical stress distribution of the 15101 gob after the modeling process.</p>
Full article ">Figure 9
<p>Simulated and measured entry displacements.</p>
Full article ">Figure 10
<p>Lateral supporting pressure in the process of mining.</p>
Full article ">Figure 11
<p>The characteristics of surrounding rock failure at different advancing distances of the working face under advanced influence.</p>
Full article ">Figure 12
<p>The failure characteristics of surrounding rock with different advancing distances in the working face under lag influence.</p>
Full article ">Figure 12 Cont.
<p>The failure characteristics of surrounding rock with different advancing distances in the working face under lag influence.</p>
Full article ">Figure 13
<p>Three-dimensional cloud maps of vertical stress of coal seam at −70 m coal pillar.</p>
Full article ">Figure 14
<p>Hydraulic fracturing borehole layout of 15102 headentry.</p>
Full article ">Figure 15
<p>Dynamic support scheme of gob-side entry driving NAWF.</p>
Full article ">Figure 16
<p>Surrounding rock cracks after hydraulic fracturing drilling.</p>
Full article ">Figure 17
<p>Roof caving characteristics before and after roof cutting in 15102 headentry.</p>
Full article ">Figure 18
<p>Control effect of 15103 tailentry.</p>
Full article ">
19 pages, 8627 KiB  
Article
Permeability Effect and Nonlinear Coupling Characteristics of Rock–Soil Interaction with Water
by Ning Liang and Ziyun Wang
Processes 2024, 12(4), 828; https://doi.org/10.3390/pr12040828 - 19 Apr 2024
Viewed by 647
Abstract
The seepage effect of rock and soil in the process of encountering water follows a nonlinear coupling law between water and rock. According to the permeability of rock and soil during softening with water, changes in particles in rock and soil are related [...] Read more.
The seepage effect of rock and soil in the process of encountering water follows a nonlinear coupling law between water and rock. According to the permeability of rock and soil during softening with water, changes in particles in rock and soil are related to permeability mechanisms. Based on the assumption of connection between particles in rock and soil, changes in particles before and after water infiltration, the mechanism of water–rock interaction, and the damage to rock and soil are analyzed herein. Combined with fractal theory and percolation theory, the random failure characteristics and nonlinear behavior of water in rock and soil are studied. At the same time, with the help of Fluent 17.0 software, the seepage process of rock samples in water is numerically simulated and analyzed. Taking the permeability coefficient of rock samples, the mass flow rate of water, and the internal pore water pressure of rock samples as tracking objects, it is found that there are obvious nonlinear characteristics in the process of water–rock interaction. The seepage–stress coupling between water and rock forms negative resistance to water seepage. The water infiltration is a slow and then accelerated process and tends to be stable. Research has shown that the coupling effect of seepage between water and rock increases the damage inside the rock and soil, and its permeability fluctuates randomly at different time steps. This feature is a common manifestation of fractal properties and percolation within rock and soil particles. At the same time, there is a non-equilibrium variation law of pore water pressure inside the rock and soil. This leads to a continuous strengthening of the seepage effect, reaching a stable state. The results of this study are crucial. It not only reveals the mechanism of interaction between water and rock but also correlates the degree of internal damage in rock and soil based on the seepage characteristics between water and rock. The conclusions can provide some reference value for relevant construction methods in the analysis of the formation of water flow characteristics, the prevention of rock slope seepage disasters, and the control of water inrush in tunnel excavation. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Permeability mechanism of rock and soil in water.</p>
Full article ">Figure 2
<p>The connection mode of particles inside rock and soil.</p>
Full article ">Figure 3
<p>Water penetration process in non-hydrophilic particles.</p>
Full article ">Figure 4
<p>Water penetration process in hydrophilic particles.</p>
Full article ">Figure 5
<p>Mechanical damage mechanism of fluid–structure interaction.</p>
Full article ">Figure 6
<p>Schematic diagram of internal void solid fractal model in rock and soil.</p>
Full article ">Figure 7
<p>Schematic diagram of internal seepage model of rock and soil.</p>
Full article ">Figure 8
<p>Finite element model of rock sample.</p>
Full article ">Figure 9
<p>Permeability coefficient in different steps.</p>
Full article ">Figure 10
<p>Schematic diagram of internal structural changes in rock and soil during seepage process. (<b>a</b>) Initial time-step size. (<b>b1</b>,<b>b2</b>) Increased time steps. (<b>c1</b>,<b>c2</b>) More time steps.</p>
Full article ">Figure 11
<p>The porosity structure inside the rock and soil: 1 open pore, 2 closed pore, 3 streamline of water.</p>
Full article ">Figure 12
<p>Mass flow rate in different steps.</p>
Full article ">Figure 13
<p>Distribution of pore water pressure in rock and soil in 100 steps. (<b>a</b>) Model S1. (<b>b</b>) Model S2.</p>
Full article ">Figure 14
<p>Distribution of pore water pressure in rock and soil in 200 steps. (<b>a</b>) Model S1. (<b>b</b>) Model S2.</p>
Full article ">Figure 15
<p>Distribution of pore water pressure in rock and soil in 500 steps. (<b>a</b>) Model S1. (<b>b</b>) Model S2.</p>
Full article ">Figure 16
<p>Pressure-drop curve at different positions of rock sample.</p>
Full article ">Figure 17
<p>Schematic diagram of particle damage in rock and soil. (<b>a</b>) Rock and Soil Sample. (<b>b</b>) Local of Sample. (<b>c</b>) Primary Seepage. (<b>d</b>) Seepage Intensification. (<b>e</b>) the Last of Seepage.</p>
Full article ">Figure 18
<p>Damage characteristics of internal structure of rock and soil under different infiltration times. (<b>a</b>) Initial state. (<b>b</b>) After a period of penetration. (<b>c</b>) After penetration for a longer time. (<b>d</b>) The last moment of penetration.</p>
Full article ">
12 pages, 3091 KiB  
Article
Design of Unmanned Road Widths in Open-Pit Mines Based on Offset Reaction Times
by Liu Han and Peng Liu
Appl. Sci. 2024, 14(7), 2995; https://doi.org/10.3390/app14072995 - 2 Apr 2024
Viewed by 831
Abstract
In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes. A significant aspect of the study is the development of a truck [...] Read more.
In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes. A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for the safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m3 and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31 m3/t. These results demonstrate that unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Open-pit end wall road: (<b>a</b>) two-lane road; (<b>b</b>) single-lane road.</p>
Full article ">Figure 2
<p>Lateral offset back to positive curve.</p>
Full article ">Figure 3
<p>Lateral dynamics model.</p>
Full article ">Figure 4
<p>End-slope mining method. A denotes the top of the slope, B denotes the upper edge of the coal seam behind the end-slope mining, C denotes the upper edge of the present coal seam, D denotes the bottom of the side slope behind the end-slope mining, and E denotes the bottom of the present slope.</p>
Full article ">Figure 5
<p>Tire model made using Trucksim.</p>
Full article ">Figure 6
<p>A 3D diagram of the Shengli West No. 1 Open-Pit Mine.</p>
Full article ">Figure 7
<p>Road width optimization of the south end slope.</p>
Full article ">Figure 8
<p>South slope stability analysis: (<b>a</b>) original slope; (<b>b</b>) optimized slope. Green indicates sandstone beds, purple marks mudstone beds, and gray-black indicates coal beds. Green striped half arcs indicate sliding surfaces.</p>
Full article ">
25 pages, 9964 KiB  
Article
Feasibility Study of Material Deformation and Similarity of Spatial Characteristics of Standard Coal Rocks
by Gang Liu, Dongwei Wang, Yonglong Zan, Shengxuan Wang and Qiqi Zhang
Processes 2024, 12(3), 454; https://doi.org/10.3390/pr12030454 - 23 Feb 2024
Viewed by 748
Abstract
The comparison between similar materials and original coal rock is the basis for similar simulation experiments in coal mines. The differences in mechanical properties, acoustic characteristics, and damage laws between similar materials and the original coal rock are of great significance for similar [...] Read more.
The comparison between similar materials and original coal rock is the basis for similar simulation experiments in coal mines. The differences in mechanical properties, acoustic characteristics, and damage laws between similar materials and the original coal rock are of great significance for similar simulation research, to reveal objective laws. First, materials similar to coal rock with similar theoretical ratios were taken as the object of research, and the sand–cement ratio, the carbon paste ratio, and the water content were determined by multivariate linear regression to accurately match the ratios. Second, by using acoustic emission and digital scattering technology to explore the acoustic law, deformation characteristics, and spatial feature similarities of the materials similar to coal rock, the acoustic emission evolution law of the original rock was found to be the same as that of the similar materials. Digital scattering was able to describe the localization of strain in the similar materials, and the correlation between the overall deformation and the local deformation was explored. This indicates that materials similar to coal rock can effectively simulate the deformation of actual coal rocks. Lastly, these materials were found to allow effectively simulating the deformation characteristics and spatial properties of actual coal rock, which provides an important experimental means and method for similar research in the field of coal rock engineering. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Preparation process of rock standard specimen.</p>
Full article ">Figure 2
<p>Similar material proportioning process.</p>
Full article ">Figure 3
<p>Prepared specimens.</p>
Full article ">Figure 4
<p>Basic mechanics of the experimental system.</p>
Full article ">Figure 5
<p>xsf9-2 stress–strain curve.</p>
Full article ">Figure 6
<p>Digital scattering method to calculate Poisson’s ratio for similar materials.</p>
Full article ">Figure 7
<p>Variation in the xsf9-2 specimen in different stages.</p>
Full article ">Figure 8
<p>Uniaxial compressive strength sensitivity analysis.</p>
Full article ">Figure 9
<p>Modulus of elasticity sensitivity analysis.</p>
Full article ">Figure 10
<p>Poisson’s ratio sensitivity analysis.</p>
Full article ">Figure 11
<p>Normal P–P plot of regression standardized residuals.</p>
Full article ">Figure 12
<p>Acoustic emission vs. stress–strain curve.</p>
Full article ">Figure 12 Cont.
<p>Acoustic emission vs. stress–strain curve.</p>
Full article ">Figure 13
<p>Digital scattering correlation method for principal strains with Carmon sheets.</p>
Full article ">Figure 13 Cont.
<p>Digital scattering correlation method for principal strains with Carmon sheets.</p>
Full article ">Figure 14
<p>Y-direction displacement cloud for the digital scattering correlation method.</p>
Full article ">Figure 15
<p>Y-direction displacement profile of the digital scattering correlation method.</p>
Full article ">
20 pages, 14650 KiB  
Article
Fractal Evolution Characteristics of Isolation Layers in a Submarine Gold Mine: A Case Study
by Yin Chen, Zijun Li, Weixing Lin, Yan He, Guoqiang Wang, Renze Ou and Qi Liu
Minerals 2024, 14(2), 205; https://doi.org/10.3390/min14020205 - 17 Feb 2024
Viewed by 737
Abstract
The establishment of an isolation layer in submarine mining has been a persistent challenge. In the context of this research, we conducted a similarity simulation test to preliminarily assess the interaction between the thickness and extent of the isolation layer. Subsequently, we introduce [...] Read more.
The establishment of an isolation layer in submarine mining has been a persistent challenge. In the context of this research, we conducted a similarity simulation test to preliminarily assess the interaction between the thickness and extent of the isolation layer. Subsequently, we introduce an innovative approach that integrates fractal theory and the Bonded Block Model (BBM) to simulate undersea isolation layer mining. The validation of this method relies on on-site borehole scanning and displacement monitoring, which depict the intricate fractal evolution of fractures and predict the optimal thickness of the isolation layer. Our findings affirm the robustness and validity of this method. Evaluation of the fractal dimensions of fractures reveals that a critical threshold of 1.7 is essential to prevent structural failure of the isolation layer, while a limit of 1.5 is necessary to avoid significant water ingress. Remarkably, the correlation dimension of the settlement time series closely aligns with the fractal dimension of the fractures, underscoring the feasibility of ensuring the safety of isolation layer mining through real-time settlement monitoring. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Geological structure diagram of the Sanshandao gold mine.</p>
Full article ">Figure 2
<p>Similar simulation test system: (<b>a</b>) similar test model, (<b>b</b>) control system.</p>
Full article ">Figure 3
<p>Arrangement of AE probe and strain gauge for similar simulation experiment.</p>
Full article ">Figure 4
<p>The gradual excavation process of the similar simulation test: (<b>a</b>) the second excavation step, (<b>b</b>) the second excavation step, (<b>c</b>) the sixth excavation step, (<b>d</b>) the ninth excavation step, (<b>e</b>) the tenth excavation step, (<b>f</b>) water inrush after ten excavation steps.</p>
Full article ">Figure 5
<p>Acoustic emission distribution and monitoring signals: (<b>a</b>) acoustic emission signal time–space distribution, (<b>b</b>) monitoring signals.</p>
Full article ">Figure 6
<p>Fracture water flow meso-process map: (<b>a</b>) initial fracture propagation, (<b>b</b>) continuous fracture propagation, (<b>c</b>) fracture water channel formation, (<b>d</b>) fracture water channel completely connected.</p>
Full article ">Figure 7
<p>Uniaxial compression test simulation for the Sanshandao gold mine: (<b>a</b>) stress-strain relation of the experiment and simulation test; (<b>b</b>) failure model with damage extent.</p>
Full article ">Figure 8
<p>Lithologies and geological structures in the model, (<b>a</b>) model profile, (<b>b</b>) model stereogram.</p>
Full article ">Figure 9
<p>Vertical displacements (contours) and fracture extensions (white lines) after excavation at different levels, with (<b>a</b>–<b>l</b>) corresponding to the excavation levels of −165 m to −55 m.</p>
Full article ">Figure 10
<p>Simulated fracturing pattern throughout the isolation layer excavation (<b>a</b>–<b>l</b>), with the red line indicating tensile fractures, the green line indicating shear fractures, and the white area indicating goafs.</p>
Full article ">Figure 11
<p>Image binarization processing of fracture extension evolution (level −155 m): (<b>a</b>) fracture propagation, (<b>b</b>) fracture binarization treatment.</p>
Full article ">Figure 12
<p>Fractal dimension around the isolation layer: (<b>a</b>) mining level −165 m; (<b>b</b>) mining level −135 m; (<b>c</b>) mining level −95 m; (<b>d</b>) mining level −45 m.</p>
Full article ">Figure 13
<p>Rock mass fracture fractal dimension with mining steps.</p>
Full article ">Figure 14
<p>Fracture flow discharge rate after excavation at different mining levels, with (<b>a</b>–<b>l</b>) corresponding to the excavation levels of −165 m to −55 m, and the white area corresponding to the goafs.</p>
Full article ">Figure 15
<p>On-site investigation of crushing zone (<b>a</b>) and water inrush in hanging wall (<b>b</b>).</p>
Full article ">Figure 16
<p>Borehole scanning and displacement monitoring point layout profile at level −155 m.</p>
Full article ">Figure 17
<p>Borehole observations of rock fractures in undersea mining: (<b>a</b>) No.01 and (<b>b</b>) No.02.</p>
Full article ">Figure 18
<p>Distribution of rock fractures in borehole scanning: (<b>a</b>) No.01 and (<b>b</b>) No.02.</p>
Full article ">Figure 19
<p>Fracture fractal dimension of boreholes: (<b>a</b>) No.01 and (<b>b</b>) No.02.</p>
Full article ">Figure 20
<p>Actual settlement and its correlation dimension, (<b>a</b>) the actual monitoring deformation of rock mass, (<b>b</b>) correlation dimension of actual deformation of rock mass.</p>
Full article ">Figure 21
<p>Simulated settlement and its correlation dimension, (<b>a</b>) the simulated deformation of rock mass, (<b>b</b>) correlation dimension of simulated deformation of rock mass.</p>
Full article ">
16 pages, 5365 KiB  
Article
Dimensionless Analysis of the Spatial–Temporal Coupling Characteristics of the Surrounding Rock Temperature Field in High Geothermal Roadway Realized by Gauss–Newton Iteration Method
by Jiale Zhou, Yuan Zhang, Peng Shi and Yang Liu
Appl. Sci. 2024, 14(4), 1608; https://doi.org/10.3390/app14041608 - 17 Feb 2024
Viewed by 565
Abstract
Understanding the time–space coupling characteristics of the surrounding rock temperature field in high geothermal roadways is essential for controlling heat damage in mines. However, current research primarily focuses on individually analyzing the temperature changes in the surrounding rock of roadways, either over time [...] Read more.
Understanding the time–space coupling characteristics of the surrounding rock temperature field in high geothermal roadways is essential for controlling heat damage in mines. However, current research primarily focuses on individually analyzing the temperature changes in the surrounding rock of roadways, either over time or space. Therefore, the Gauss–Newton iteration method is employed to model the coupling relationship between temperature, time, and space. The results demonstrate that the dual coupling function describing the temperature field of the surrounding rock in both time and space provides a more comprehensive characterization of the temperature variations. Over time, as ventilation duration increases, the fitting degree of the characteristic curve steadily rises, and the characteristic curve descends overall. In the spatial dimension, the fitting degree of the characteristic curve gradually decreases with the rise of the dimensionless radius, and the characteristic curve ascends overall. Additionally, as thermal conductivity increases, the fitting degree of the characteristic curve steadily rises. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Temperature field two-dimensional model of surrounding rock of roadway with high geothermal.</p>
Full article ">Figure 2
<p>The relationship curve between <span class="html-italic">R</span> and parameters E, G, and H.</p>
Full article ">Figure 3
<p>The relationship curve between dimensionless temperature and dimensionless radius.</p>
Full article ">Figure 4
<p>The relationship curve between dimensionless temperature and dimensionless time.</p>
Full article ">Figure 5
<p>The relationship between dimensionless temperature and dimensionless radius under different thermal conductivities.</p>
Full article ">Figure 6
<p>The relationship between dimensionless temperature and dimensionless time under different thermal conductivity.</p>
Full article ">Figure 7
<p>The characteristic curves of dimensionless temperature and dimensionless radius at different depths.</p>
Full article ">Figure 8
<p>The characteristic curves of dimensionless temperature and dimensionless time at different depths.</p>
Full article ">Figure 9
<p>The characteristic curves of dimensionless temperature and dimensionless radius at different thermal conductivities. (<b>a</b>) 1 day; (<b>b</b>) 31 days; (<b>c</b>) 181 days; (<b>d</b>) 361 days.</p>
Full article ">Figure 10
<p>The characteristic curves of dimensionless temperature and dimensionless time at different thermal conductivity. (<b>a</b>) 0.1 <span class="html-italic">R</span>; (<b>b</b>) 1 <span class="html-italic">R</span>; (<b>c</b>) 2 <span class="html-italic">R</span>; (<b>d</b>) 3 <span class="html-italic">R</span>.</p>
Full article ">
0 pages, 4776 KiB  
Article
Simulation Study on Dynamic Characteristics of the Chain Drive System for Mining Scraper Conveyor Driven by the Permanent Magnet Synchronous Motor
by Xi Zhang, Mingming Ren, Hongju Wang and Lei Jin
Processes 2024, 12(1), 165; https://doi.org/10.3390/pr12010165 - 10 Jan 2024
Viewed by 1292
Abstract
The chain drive system represents a critical subsystem within the scraper conveyor. This paper proposes a joint simulation model for the drive system of the scraper conveyor, driven by the permanent magnet synchronous motor, in order to conduct a comprehensive analysis of the [...] Read more.
The chain drive system represents a critical subsystem within the scraper conveyor. This paper proposes a joint simulation model for the drive system of the scraper conveyor, driven by the permanent magnet synchronous motor, in order to conduct a comprehensive analysis of the dynamic characteristics of the chain drive system during the operational process. Firstly, the dynamic simulation model for the mining scraper conveyor’s chain drive system was established in ADAMS, taking into account its structural characteristics. Then, the mathematical model of the permanent magnet synchronous motor was established using the coordinate transformation theory, and the speed controller based on vector control was designed by using the theory related to sliding mode control. The coupling relationship between the chain drive system of the scraper conveyor and the permanent magnet synchronous motor drive system was investigated. Finally, a joint simulation model of the mechanical system and motor control system was created using ADAMS (View 2019) and MATLAB/Simulink (2020a). The dynamic characteristics of the chain drive system were analyzed, and the three typical working conditions of no load, half load, and rated load were considered. The results show that the contact force between the flat ring and the sprocket undergoes an initial increase, followed by a decrease, and finally another increase. As the load increases from no load to full load, there is a marked increase in the contact force between the loaded side chainrings. Due to the polygon effect, both the speed curve of the permanent magnet drive motor and the contact force curve between the ring chains exhibit periodic fluctuations. The research in this paper provides an idea for the coupling analysis of the scraper conveyor electromechanical system. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Simplified model of scraper conveyor chain drive system.</p>
Full article ">Figure 2
<p>Restriction of the system.</p>
Full article ">Figure 3
<p>Block diagram of the PMSM control system. (<span class="html-italic">ω<sub>r</sub>*</span> is the target speed, <span class="html-italic">i<sub>q</sub>*</span> is the q-axis current component regulated by the PI controller, and <span class="html-italic">i<sub>d</sub>*</span> is the given d-axis current component.)</p>
Full article ">Figure 4
<p>Simulation model of the PMSM control system.</p>
Full article ">Figure 5
<p>Block diagram of electromechanical joint simulation model of PMSM-driven scraper conveyor.</p>
Full article ">Figure 6
<p>Preset speed curve of the PMSM.</p>
Full article ">Figure 7
<p>Simulation curve of motor speed under no-load condition (N1: speed of head motor, N2: speed of tail motor).</p>
Full article ">Figure 8
<p>Simulation curve under no-load condition. (<b>a</b>) Horizontal contact force between the flat ring and the vertical ring; (<b>b</b>) contact force between the flat ring and the sprocket; (<b>c</b>) contact force between the four flat rings and the head sprocket in the engagement zone.</p>
Full article ">Figure 9
<p>Simulation curve of motor speed under half-load condition (N1: speed of head motor, N2: speed of tail motor).</p>
Full article ">Figure 10
<p>Simulation curve under half-load condition. (<b>a</b>) Horizontal contact force between the flat ring and the vertical ring; (<b>b</b>) contact force between the flat ring and the sprocket; (<b>c</b>) contact force between the four flat rings and the head sprocket in the engagement zone.</p>
Full article ">Figure 11
<p>Simulation curve of motor speed under rated load condition (N1: speed of head motor, N2: speed of tail motor).</p>
Full article ">Figure 12
<p>Simulation curve under rated load condition. (<b>a</b>) Horizontal contact force between the flat ring and the vertical ring; (<b>b</b>) contact force between the flat ring and the sprocket; (<b>c</b>) contact force between the four flat rings and the head sprocket in the engagement zone.</p>
Full article ">Figure 12 Cont.
<p>Simulation curve under rated load condition. (<b>a</b>) Horizontal contact force between the flat ring and the vertical ring; (<b>b</b>) contact force between the flat ring and the sprocket; (<b>c</b>) contact force between the four flat rings and the head sprocket in the engagement zone.</p>
Full article ">
14 pages, 1962 KiB  
Article
Energy Accumulation Law of Different Forms of Coal–Rock Combinations
by Zibo Li, Guohua Zhang, Yubo Li, Wenjun Zhou, Tao Qin, Li Zeng and Gang Liu
Appl. Sci. 2023, 13(20), 11393; https://doi.org/10.3390/app132011393 - 17 Oct 2023
Viewed by 772
Abstract
Coal–rock disasters are becoming more and more severe as the intensity of coal mining increases. Due to its destructive power and resulting extensive area damage, rock burst is among the most critical threats to coal mine safety. It results from the combined action [...] Read more.
Coal–rock disasters are becoming more and more severe as the intensity of coal mining increases. Due to its destructive power and resulting extensive area damage, rock burst is among the most critical threats to coal mine safety. It results from the combined action of the coal and the rock when affected by the mining process. To this end, we used a combination of coal and rock to conduct our studies. Combining a uniaxial compression experiment with theoretical analysis, this work investigated how different lithologies and coal–rock height ratios affect the mechanical properties of this combination and the law governing energy accumulation. We determined the following: When the coal–rock height ratios are dissimilar, the peak strength and modulus of elasticity of the combination show a negative correlation with the coal thickness share, and the pre-peak energy accumulation and impact energy index of the combination is positively correlated with the coal thickness percentage. In combination with the same coal–rock height ratio, the peak strength, elastic modulus, pre-peak energy accumulation, and impact energy index all increase with increased rock strength and elastic modulus. The presence of a hard rock layer affects the accumulation of pre-peak energy. Based on the experimental analysis, a theoretical model was established, and the surrounding rock stress negatively correlates with the percentage of coal thickness; the energy stored in the surrounding rock is directly proportional to the coal in the zone. Therefore, we inferred that the stress distribution of the surrounding rock as coal thickness changes is abnormal; substantial energy accumulation can swiftly initiate dynamic disasters, such as rock bursts. This study has important reference significance for preventing and controlling rock bursts in areas where coal thickness changes. Full article
(This article belongs to the Topic New Advances in Mining Technology)
Show Figures

Figure 1

Figure 1
<p>Combination model and wave velocity measurement.</p>
Full article ">Figure 2
<p>Part of the sample physical picture.</p>
Full article ">Figure 3
<p><span class="html-italic">σ</span>-<span class="html-italic">ε</span> curves of different coal–rock combinations. (<b>a</b>) Coal and rock monomer; (<b>b</b>) SC combination; (<b>c</b>) FC combination; (<b>d</b>) FSC combination.</p>
Full article ">Figure 4
<p>Distribution characteristics of peak strength and elastic modulus of different combinations.</p>
Full article ">Figure 5
<p>The relationship between peak strength, elastic modulus, and coal–rock thickness ratio of the combination. (<b>a</b>) Combination <span class="html-italic">σ</span><sub>1</sub>; (<b>b</b>) Combination <span class="html-italic">E</span>.</p>
Full article ">Figure 6
<p>Energy variation of different coal–rock combinations.</p>
Full article ">Figure 7
<p>The energy variation of the combinations with different coal thicknesss. (<b>a</b>) pre-peak energy distribution; (<b>b</b>) post-peak energy distribution; (<b>c</b>) impact energy index.</p>
Full article ">Figure 8
<p>Energy variation of different lithologic combinations. (<b>a</b>) Average pre-peak energy; (<b>b</b>) Average post-peak energy; (<b>c</b>) Impact energy index.</p>
Full article ">Figure 9
<p>Coal–rock combination model.</p>
Full article ">Figure 10
<p>Relationship between the energy of coal–rock combinations and the ratio of coal thickness.</p>
Full article ">Figure 11
<p>Coal thickness change model.</p>
Full article ">
Back to TopTop