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20 pages, 15749 KiB  
Article
Study on the Vibration Propagation Law and Stress Distribution Characteristics in Double-Arch Tunnels During Blasting
by Xiaofei Sun, Ying Su, Dunwen Liu, Yu Tang, Pei Zhang, Jishuang Hu and Xianghao Sun
Buildings 2025, 15(1), 139; https://doi.org/10.3390/buildings15010139 - 5 Jan 2025
Viewed by 390
Abstract
Highway tunnel construction in mountainous areas of China has been developing rapidly. The influence of drilling and blasting on the existing tunnel structure has become a key factor affecting the safety and stability of tunnel construction. The double-arch tunnel has unique structural characteristics. [...] Read more.
Highway tunnel construction in mountainous areas of China has been developing rapidly. The influence of drilling and blasting on the existing tunnel structure has become a key factor affecting the safety and stability of tunnel construction. The double-arch tunnel has unique structural characteristics. The propagation characteristics of blasting vibrations and the resulting stress responses exhibit a certain level of complexity. There is little research on the influence of single-line blasting excavation of double-arch tunnel on the other line tunnel. This paper analyzes the blasting vibration of a double-arch tunnel by ANSYS/LS-DYNA. The propagation law of blasting vibration velocity and stress distribution law of blasting vibration in different sections of the tunnel is revealed. At the same time, the relationship between the peak particle velocity (PPV) and tensile stress is established, and the threshold vibration velocity is proposed. It provides a scientific basis for tunnel design and construction. The propagation of blasting vibration in the adjacent roadway is affected by the middle pilot tunnel. The peak vibration velocity of different parts decreases with the increase in distance. The monitoring of vibration velocity and stress in section A of the right line of the adjacent tunnel should be strengthened, especially in the tunnel vault, blast-facing side wall, and arch foot. The difference in vibration strength across different tunnel parts provides a basis for optimizing the structure. It helps strengthen the parts susceptible to vibration during the design stage of the multi-arch tunnel, improving the tunnel’s safety and stability. Full article
(This article belongs to the Special Issue Dynamic Response of Civil Engineering Structures under Seismic Loads)
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Figure 1
<p>Borehole layout.</p>
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<p>The Blast-UM blasting vibrometer.</p>
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<p>Flowchart.</p>
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<p>The layout of the monitoring points.</p>
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<p>On-site monitoring equipment.</p>
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<p>Vibration diagram.</p>
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<p>PPV–frequency.</p>
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<p>Simulation result.</p>
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<p>Simulation result.</p>
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<p>Mesh fineness.</p>
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<p>Mesh quality.</p>
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<p>Material condition.</p>
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<p>Simulated vibration velocity on the blast-facing side.</p>
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<p>Simulated vibration velocity on the blast-opposite side.</p>
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<p>Effect of smooth blasting.</p>
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<p>Blast vibration propagation diagram.</p>
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<p>Section and selected points distribution diagram.</p>
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<p>The PPV distribution diagram 1.</p>
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<p>The PPV distribution diagram 2.</p>
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<p>Distribution of effective stresses.</p>
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<p>Unit selection and naming.</p>
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<p>Variation law of effective stresses.</p>
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<p>Maximum tensile stress–PPV.</p>
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22 pages, 2873 KiB  
Article
Safety Assessment of the Cover-and-Cut Method Under Blasting Vibration Induced by Tunnel Excavation
by Yunhao Che and Enan Chi
Appl. Sci. 2025, 15(1), 260; https://doi.org/10.3390/app15010260 - 30 Dec 2024
Viewed by 329
Abstract
In evaluating the construction safety of the building in the subway tunnel using the cover-and-cut method, the main objective is to analyze the diaphragm wall, the central pillar, and the roof. This article conducted a blasting vibration test based on the background of [...] Read more.
In evaluating the construction safety of the building in the subway tunnel using the cover-and-cut method, the main objective is to analyze the diaphragm wall, the central pillar, and the roof. This article conducted a blasting vibration test based on the background of the Guiyang Metro Line 3 project and used the FLAC3D software to establish a three-dimensional numerical model. The results showed that the peak particle velocity (PPV) decreased with increasing distance from the blasting center. The PPV measured at the underground diaphragm wall was 1.424 cm/s, while at the bottom of the central pillar it was 1.482 cm/s. The predicted PPV on the roof was up to 1.537 cm/s, which met the safety standards. According to the cloud map of particle vibration velocity and the comprehensive analysis of particle vibration velocity, the degree of impact of artificial structures in the subway tunnel was the central pillar, the underground diaphragm wall, and the roof in order from high to low. After eight blasting operations per day, the vibration velocity trend at the vulnerable point of the central column increases, but it will not exceed the safety standard. Full article
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<p>GuiYang subway line 3 layout.</p>
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<p>Section of the subway tunnel in the cover-and-cut method.</p>
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<p>Blast hole and delay layout diagram.</p>
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<p>Finite element model of the tunnel structure.</p>
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<p>The diagram of a triangular shock wave load curve.</p>
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<p>Layout of the monitoring points.</p>
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<p>Simulation of the vibration speed of the diaphragm wall measurement point.</p>
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<p>Vibration speed peak of the bottom measuring point at the bottom of the neutral column.</p>
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<p>Diaphragm wall measurement diagram.</p>
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<p>Comparison of PPV curves between numerically simulation and field test on the No. 6 point.</p>
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<p>Main vibration frequency of the monitoring points.</p>
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<p>Metro tunnel vibration speed cloud map.</p>
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<p>Peak values of particle vibration velocity at different measurement.</p>
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<p>Regression relationship between peak particle velocity (PPV) at point 11 and blasting frequency.</p>
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17 pages, 4261 KiB  
Article
A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions
by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li and Jiawen Sun
Mathematics 2024, 12(24), 3971; https://doi.org/10.3390/math12243971 - 17 Dec 2024
Viewed by 404
Abstract
Currently, numerous intelligent maximum power point tracking (MPPT) algorithms are capable of tackling the global optimization challenge of multi-peak photovoltaic output power under partial shading conditions, yet they often face issues such as slow convergence, low tracking precision, and substantial power fluctuations. To [...] Read more.
Currently, numerous intelligent maximum power point tracking (MPPT) algorithms are capable of tackling the global optimization challenge of multi-peak photovoltaic output power under partial shading conditions, yet they often face issues such as slow convergence, low tracking precision, and substantial power fluctuations. To address these challenges, this paper introduces a hybrid algorithm that integrates an improved salp swarm algorithm (SSA) with the perturb and observe (P&O) method. Initially, the SSA is augmented with a dynamic spiral evolution mechanism and a Lévy flight strategy, expanding the search space and bolstering global search capabilities, which in turn enhances the tracking precision. Subsequently, the application of a Gaussian operator for distribution calculations allows for the adaptive adjustment of step sizes in each iteration, quickening convergence and diminishing power oscillations. Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude. Full article
(This article belongs to the Special Issue Advances in Control Systems and Automatic Control)
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<p>Output characteristic curves of PV array at different irradiances.</p>
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<p>Flowcharts of (<b>a</b>) the ISSA algorithm and (<b>b</b>) the overall ISSA-P&amp;O algorithm.</p>
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<p>Overall structure of the ISSA-P&amp;O-based MPPT of the PV system.</p>
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<p>The power tracking curves under steady weather conditions. (<b>a</b>) PSO, (<b>b</b>) GWO, (<b>c</b>) SSA, and (<b>d</b>) ISSA-P&amp;O.</p>
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<p>Tracking power error over time. (<b>a</b>) PSO, (<b>b</b>) GWO, (<b>c</b>) SSA, and (<b>d</b>) ISSA-P&amp;O.</p>
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<p>The power tracking curves under dynamic weather conditions. (<b>a</b>) PSO, (<b>b</b>) GWO, (<b>c</b>) SSA, and (<b>d</b>) ISSA-P&amp;O.</p>
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<p>Experimental platform.</p>
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<p>Experimental output voltage tracking curves under steady weather conditions. (<b>a</b>) P&amp;O and (<b>b</b>) ISSA-P&amp;O.</p>
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<p>Experimental output voltage tracking curves under dynamic weather conditions. (<b>a</b>) P&amp;O and (<b>b</b>) ISSA-P&amp;O.</p>
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15 pages, 6881 KiB  
Article
Experimental Study on the Changes to the Microstructures and Dynamic Mechanical Properties of Layered Sandstone After High-Temperature Treatment
by Shang Gao, Yueyu Wu and Xuqing Yang
Appl. Sci. 2024, 14(24), 11729; https://doi.org/10.3390/app142411729 - 16 Dec 2024
Viewed by 479
Abstract
In this study, changes in the basic physical properties, mineral composition, mass, and microstructure of layered sandstone were evaluated following heat treatment at 200–800 °C. Dynamic impact compression tests were performed using a split-Hopkinson pressure bar test system (SHPB), and digital image correlation [...] Read more.
In this study, changes in the basic physical properties, mineral composition, mass, and microstructure of layered sandstone were evaluated following heat treatment at 200–800 °C. Dynamic impact compression tests were performed using a split-Hopkinson pressure bar test system (SHPB), and digital image correlation (DIC) was used to monitor the dynamic failure processes of the involved specimens. Results indicate that high-temperature treatment reduces the mass, wave velocity and peak stress of layered sandstone; increases the porosity, pore length, and pore aperture. The rates of decrease in the wave velocity and peak stress considerably increase with increasing temperature above a threshold of 400 °C. This is because at temperatures above 400 °C, thermal cracks will form both between and within particles. As the number of cracks increases, they will propagate and connect with each other, forming a network of cracks. DIC results show that as the heat treatment temperature rises, the range of the strain-concentration areas, which are formed by sandstone failures, substantially expands. However, the increase in the heat treatment temperature only negligibly influences the propagation direction of primary sandstone cracks, which mainly propagate along the weak bedding planes. Full article
(This article belongs to the Topic Exploitation and Underground Storage of Oil and Gas)
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Figure 1
<p>Layered sandstone core specimen and optical microscopy images of the specimen core. (<b>a</b>) Image of the layered sandstone core; (<b>b</b>) relationship between the bedding plane and loading directions; (<b>c</b>) reflected light image of layered sandstone under the microscope; and (<b>d</b>) transmitted light image of layered sandstone under the orthogonal polarization system.</p>
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<p>SHPB impact test system setup.</p>
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<p>Stress equilibrium diagram.</p>
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<p>Changes in color of layered sandstone after high-temperature treatment.</p>
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<p>Mass loss rate (<b>a</b>) and longitudinal wave velocity reduction rate (<b>b</b>) in layered sandstone under different temperature conditions.</p>
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<p>XRD analysis of layered sandstone after high-temperature treatment.</p>
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<p>TG and DTG curves of layered sandstone.</p>
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<p>Microstructural characteristics of layered sandstone heat-treated at different temperatures. (<b>a</b>,<b>b</b>) Rock sample at room temperature; (<b>c</b>) Rock sample heated at 200 °C; (<b>d</b>) Rock sample heated at 400 °C; (<b>e</b>) Rock sample heated at 600 °C; (<b>f</b>) Rock sample heated at 800 °C.</p>
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<p>CT images of layered sandstone. (<b>a</b>) Two-dimensional images of sandstone core slices obtained via threshold segmentation. (<b>b</b>) Three-dimensional reconstructions of the pore distribution in layered sandstone core.</p>
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<p>Static stress–strain curves of layered sandstone.</p>
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<p>Dynamic stress–strain curves of layered sandstone.</p>
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<p>Variation of the dynamic compressive strength (<b>a</b>) and dynamic elastic modulus of layered sandstone (<b>b</b>).</p>
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<p>Impact fracture characteristics of bedding sandstone after high-temperature treatment.</p>
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<p>Images of the sandstone failure process and strain field evolution nephograms after layered sandstone is heat-treated at different temperatures. (<b>a</b>) Rock sample at room temperature; (<b>b</b>) Rock sample heated at 200 °C; (<b>c</b>) Rock sample heated at 400 °C; (<b>d</b>) Rock sample heated at 600 °C; (<b>e</b>) Rock sample heated at 800 °C.</p>
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14 pages, 8788 KiB  
Article
Influence of a Frame Structure Building Demolition on an Adjacent Subway Tunnel: Monitoring and Analysis
by Wei Wang, Xianqi Xie, Fang Yuan, Peng Luo, Yue Wu, Changbang Liu and Senlin Nie
Buildings 2024, 14(12), 3974; https://doi.org/10.3390/buildings14123974 - 14 Dec 2024
Viewed by 496
Abstract
In a complex urban environment, the impact of building demolitions by blasting on the structural integrity of nearby metro tunnels is critical. This study systematically analyzed the blasting and demolition process of a building adjacent to a metro tunnel using various monitoring methods, [...] Read more.
In a complex urban environment, the impact of building demolitions by blasting on the structural integrity of nearby metro tunnels is critical. This study systematically analyzed the blasting and demolition process of a building adjacent to a metro tunnel using various monitoring methods, including blasting vibration, dynamic strain, deformation and settlement, pore water pressure, and displacement. The results indicate that the metro tunnel’s vibration response can be divided into four stages: notch blasting, notch closure, overall collapse impact, and auxiliary notch blasting. The most significant impact on the tunnel segments occurred during the building’s ground impact phase, with a peak particle velocity of 0.57 cm/s. The maximum tensile and compressive stresses induced in the tunnel segments did not exceed 0.4 MPa, well within the safety limits. Displacement and settlement changes in the tunnel structure were less than 1 mm, far below the warning threshold. Additionally, blasting vibrations significantly affected the pore water pressure in the surrounding soil. However, fluctuations caused by ground impact vibrations were minimal, and the pore water pressure quickly returned to its initial level after the blasting concluded. Throughout the process, no adverse effects on the metro tunnel structure were observed. Full article
(This article belongs to the Section Building Structures)
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<p>Position relationship between the building and the subway tunnel (unit: m).</p>
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<p>Blasting cut of mechanical edifice (unit: mm).</p>
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<p>Vibration monitoring point layout: (<b>a</b>) Vibration monitoring point layout; (<b>b</b>) On-site layout of hall and track bed.</p>
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<p>Segment dynamic strain monitoring record: (<b>a</b>) Monitoring section layout; (<b>b</b>) DH8302 type dynamic strain gauge; (<b>c</b>) Strain gauge site layout.</p>
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<p>Tunnel deformation and settlement monitoring records: (<b>a</b>) Monitoring point mark; (<b>b</b>) Section monitoring point records; (<b>c</b>) Tunnel 3D laser scanning.</p>
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<p>Pore water pressure and displacement monitoring records: (<b>a</b>). Monitoring point layout; (<b>b</b>) Equipment placement hole coring; (<b>c</b>). Installation of pore water pressure gauge.</p>
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<p>Inclinometer principle.</p>
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<p>Vibration speed of each measuring point: (<b>a</b>) 2# vibration speed; (<b>b</b>) 3# vibration speed; (<b>c</b>) 4# vibration speed; (<b>d</b>) 5# vibration speed; (<b>e</b>) 6# vibration speed.</p>
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<p>Vibration velocity result division.</p>
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<p>Dynamic strain of each measuring point: (<b>a</b>) 1# left strain; (<b>b</b>) 1# right strain; (<b>c</b>) 2# left strain; (<b>d</b>) 2# right strain; (<b>e</b>) 3# left strain; (<b>f</b>) 3# right strain.</p>
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<p>Peak displacement variation diagram.</p>
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<p>Pore water pressure changes.</p>
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<p>Horizontal displacement changes with depth.</p>
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<p>The collapse process of the mechanical edifice.</p>
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<p>The muck pile of mechanical edifice.</p>
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19 pages, 3298 KiB  
Article
Quantitative Characterization Method of Additional Resistance Based on Suspended Particle Migration and Deposition Model
by Huan Chen, Yanfeng Cao, Jifei Yu, Xiaopeng Zhai, Jianlin Peng, Wei Cheng, Tongchuan Hao, Xiaotong Zhang and Weitao Zhu
Energies 2024, 17(24), 6246; https://doi.org/10.3390/en17246246 - 11 Dec 2024
Viewed by 323
Abstract
The phenomenon of pore blockage caused by injected suspended particles significantly impacts the efficiency of water injection and production capacity release in offshore oilfields, leading to increased additional resistance during the injection process. To enhance water injection volumes in injection wells, it is [...] Read more.
The phenomenon of pore blockage caused by injected suspended particles significantly impacts the efficiency of water injection and production capacity release in offshore oilfields, leading to increased additional resistance during the injection process. To enhance water injection volumes in injection wells, it is essential to quantitatively study the additional resistance caused by suspended particle blockage during water injection. However, there is currently no model for calculating the additional resistance resulting from suspended particle blockage. Therefore, this study establishes a permeability decline model based on the microscopic dispersion kinetic equation of particle transport. The degree of blockage is characterized by the reduction in fluid volume, and the additional resistance caused by particle migration and blockage during water injection is quantified based on the fluid volume decline. This study reveals that over time, suspended particles do not continuously migrate deeper into the formation but tend to deposit near the wellbore, blocking pores and increasing additional resistance. Over time, the concentration of suspended particles near the wellbore approaches the initial concentration of the injected water. An increase in seepage velocity raises the peak concentration of suspended particles, but when the seepage velocity reaches a certain threshold, its effect on particle migration stabilizes. The blockage location of suspended particles near the wellbore is significantly influenced by seepage velocity and time. An increase in particle concentration and size accelerates blockage formation but does not change the blockage location. As injection time increases, the fitted injection volume and permeability exhibit a power-law decline. Based on the trend of injection volume reduction, the additional resistance caused by water injection is calculated to range between 0 and 3.85 MPa. Engineering cases indicate that blockages are challenging to remove after acidification, and the reduction in additional resistance is limited. This study provides a quantitative basis for understanding blockage patterns during water injection, helps predict changes in additional resistance, and offers a theoretical foundation for targeted treatment measures. Full article
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<p>Schematic diagram of the process of suspended particle transport, deposition, and clogging.</p>
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<p>Flowchart for calculating additional resistance.</p>
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<p>Experimental setup and flowchart.</p>
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<p>Clogging degree of suspended particles at different positions under varying time conditions. (<b>a</b>) Particle deposition concentration from 50 cm to 200 cm from the inlet; (<b>b</b>) Particle deposition concentration from400 cm to 800 cm from the inle.</p>
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<p>Distribution of suspended particles under different concentration conditions.</p>
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<p>Distribution of suspended particles under different permeabilities.</p>
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<p>Distribution of suspended particles under different particle size condition velocities.</p>
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<p>Permeability of different particle diameters.</p>
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<p>Analysis of additional resistance in the first acidizing stage for well SZ-1-34. (<b>a</b>) Water injection pressure and injection volume curves; (<b>b</b>) Water injection blockage location; (<b>c</b>) Permeability change after blockage; (<b>d</b>) Injection volume change after blockage; (<b>e</b>) Skin factor and additional resistance changes after blocking.</p>
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<p>Analysis of additional resistance in the second acidizing stage for well SZ-1-34. (<b>a</b>) Permeability change after blockage; (<b>b</b>) Injection volume change after blockage; (<b>c</b>) Skin factor and additional resistance changes after blocking.</p>
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<p>Analysis of additional resistance in the first acidizing stage of well SZ-1-12. (<b>a</b>) Water injection pressure and injection volume curves; (<b>b</b>) Water injection blockage location; (<b>c</b>) Permeability change after blockage; (<b>d</b>) Injection volume change after blockage; (<b>e</b>) Skin factor and additional resistance changes after blocking.</p>
Full article ">Figure 11 Cont.
<p>Analysis of additional resistance in the first acidizing stage of well SZ-1-12. (<b>a</b>) Water injection pressure and injection volume curves; (<b>b</b>) Water injection blockage location; (<b>c</b>) Permeability change after blockage; (<b>d</b>) Injection volume change after blockage; (<b>e</b>) Skin factor and additional resistance changes after blocking.</p>
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<p>Analysis of additional resistance during the second acidizing stage for well SZ-1-12. (<b>a</b>) Permeability change after blockage; (<b>b</b>) Injection volume change after blockage; (<b>c</b>) Skin factor and additional resistance changes after blocking.</p>
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23 pages, 10122 KiB  
Article
Effect of the Cross-Sectional Geometry of the Mixed Particle Zone on the Spiral Separation Process and Its Structural Optimization
by Shuling Gao, Qian Wang, Xiaohong Zhou, Chunyu Liu, Yanbai Shen and Baoyu Cui
Minerals 2024, 14(12), 1251; https://doi.org/10.3390/min14121251 - 9 Dec 2024
Viewed by 456
Abstract
Cross-sectional geometry is of significance in determining the flow characteristics and the particles separation in spiral concentrators. The effects of the cross-sectional geometry within the mixed particle zone on the secondary flow and the separation process of hematite and quartz particles with a [...] Read more.
Cross-sectional geometry is of significance in determining the flow characteristics and the particles separation in spiral concentrators. The effects of the cross-sectional geometry within the mixed particle zone on the secondary flow and the separation process of hematite and quartz particles with a size of 89.5 μm were investigated via a computational fluid dynamics (CFD) approach. The optimization of the line segment slopes was conducted using response surface methodology (RSM). The results indicate that the peak radial fluxes and average radial velocities of the secondary flow are positively correlated with the corresponding line segment slope. The independent adjustment of line slopes in regions I and II, and the interaction of line slopes in regions I and III, influence the separation efficiency of hematite and quartz particles significantly. The separation performance of the experimental spiral concentrator with a cross-sectional profile of the optimized line segments for a feed of hematite and quartz with a size range of −100 + 75 μm is remarkably improved by nearly 5%. This study provides insights for the cross-section design of spiral concentrators for the effective separation of coarse-grained hematite and quartz. Full article
(This article belongs to the Special Issue Advances in the Theory and Technology of Physical Separation)
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Graphical abstract

Graphical abstract
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<p>Schematic of the cross-sectional geometry of the spiral concentrator.</p>
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<p>Effects of the cross-sectional geometry parameters on the separation efficiency. (<b>a</b>) Effect of the downwards bevel angle; (<b>b</b>) effect of the sectional curve function; (<b>c</b>) interaction between the downwards bevel angle and the sectional curve function.</p>
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<p>Yield distribution and separation efficiency of hematite and quartz at the end of the third turn. (<b>a</b>) Yield Distribution; (<b>b</b>) separation efficiency.</p>
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<p>Resegmentation of the cross-sectional geometry of the mixed particle zone.</p>
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<p>Particle size composition of the feed to the spiral separator at the Qidashan Iron Mine Processing Plant.</p>
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<p>Computational domain mesh of spiral separator. (<b>a</b>) Mesh of one turn; (<b>b</b>) mesh of the cross-section.</p>
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<p>Computational domain mesh of spiral separator. (<b>a</b>) Mesh of one turn; (<b>b</b>) mesh of the cross-section.</p>
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<p>Mesh independence test.</p>
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<p>Effect of the line segment slope in region I on the radial fluxes of the inward and outward flows at <span class="html-italic">r</span> = 80 mm. (<b>a</b>) Radial flux of the inward flow; (<b>b</b>) radial flux of the outward flow.</p>
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<p>Effects of the line segment slope in region II on the radial fluxes of the inward and outward flows at <span class="html-italic">r</span> = 100 mm. (<b>a</b>) Radial flux of the inward flow; (<b>b</b>) radial flux of the outward flow.</p>
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<p>Effects of the line segment slope in region III on the radial fluxes of the inward and outward flows at <span class="html-italic">r</span> = 120 mm. (<b>a</b>) Radial flux of the inward flow; (<b>b</b>) radial flux of the outward flow.</p>
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<p>Effect of the line segment slopes in the localized region on the average radial velocity of the inward and outward flows in the third turn with different radial regions. (<b>a</b>) Region I; (<b>b</b>) region II; (<b>c</b>) region III.</p>
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<p>Effect of the line segment slope in region I on the cumulative radial flux at <span class="html-italic">r</span> = 80 mm. (<b>a</b>) Hematite; (<b>b</b>) quartz.</p>
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<p>Effect of the line segment slope in region II on the cumulative radial flux at <span class="html-italic">r</span> = 100 mm. (<b>a</b>) Hematite; (<b>b</b>) quartz.</p>
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<p>Effect of the line segment slope in region III on the cumulative radial flux at <span class="html-italic">r</span> = 120 mm. (<b>a</b>) Hematite; (<b>b</b>) quartz.</p>
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<p>Effect of the localized line segment slope on the separation performance of the spiral separator. (<b>a</b>) Region I; (<b>b</b>) region II; (<b>c</b>) region III.</p>
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<p>Correlations between the values obtained from numerical simulation and the values predicted by the regression model.</p>
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<p>Three-dimensional response surface of the effects of the three factors on the maximum separation efficiency when the three factors interact in pairs. (<b>a</b>) Interaction of region I with region II; (<b>b</b>) interaction of region I with region III; (<b>c</b>) interaction of region II with region III.</p>
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<p>Spiral concentrator test equipment and separation test system. (<b>a</b>) Two optimized spiral concentrators; (<b>b</b>) systems for separation tests in spiral concentrators.</p>
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<p>Comparison of the separation efficiency at various splitter positions for two types of spiral concentrators. (<b>a</b>) Optimal continuous curve section; (<b>b</b>) optimal combined line segment section.</p>
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<p>Variation curves of the cumulative radial flux of particles in spiral concentrators with different cross-sections. (<b>a</b>) <span class="html-italic">r</span> = 80 mm; (<b>b</b>) <span class="html-italic">r</span> = 100 mm; (<b>c</b>) <span class="html-italic">r</span> = 120 mm.</p>
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10 pages, 2220 KiB  
Article
Prediction of Blast Vibration Velocity of Buried Steel Pipe Based on PSO-LSSVM Model
by Hongyu Zhang, Shengwu Tu, Senlin Nie and Weihua Ming
Sensors 2024, 24(23), 7437; https://doi.org/10.3390/s24237437 - 21 Nov 2024
Viewed by 381
Abstract
In order to ensure the safe operation of adjacent buried pipelines under blast vibration, it is of great practical engineering significance to accurately predict the peak vibration velocity ofburied pipelines under blasting loads. Relying on the test results of the buried steel pipe [...] Read more.
In order to ensure the safe operation of adjacent buried pipelines under blast vibration, it is of great practical engineering significance to accurately predict the peak vibration velocity ofburied pipelines under blasting loads. Relying on the test results of the buried steel pipe blast model test, a sensitivity analysis of relevant influencing factors was carried out by using the gray correlation analysis method. A least squares support vector machine (LS-SVM) model was established to predict the peak vibration velocity of the pipeline and determine the best parameter combination in the LS-SVM model through a local particle swarm optimization (PSO), and the results of the PSO-LSSVM model were predicted. These were compared with BP neural network model and Sa’s empirical formula. The results show that the fitting correlation coefficient (R2), root mean square error (RMSE), average relative error (MRE), and Nash coefficient (NSE) of the PSO-LSSVM model for the prediction of pipeline peak vibration velocity are 91.51%, 2.95%, 8.69%, and 99.03%, showing that the PSO-LSSVM model has a higher prediction accuracy and better generalization ability, which provides a new idea for the vibration velocity prediction of buried pipelines under complex blasting conditions. Full article
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<p>Processing flow of PSO-LSSVM model.</p>
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<p>Model test layout diagram.</p>
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<p>Installation diagram of blast vibration meter.</p>
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<p>Fitness curve of PSO-LSSVM model.</p>
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<p>A comparison between the true value and the predicted value of the training sample of the PSO-LSSVM model.</p>
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<p>Comparison of prediction results of different models.</p>
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17 pages, 5119 KiB  
Article
Insights into Microscopic Characteristics of Gasoline and Ethanol Spray from a GDI Injector Under Injection Pressure up to 50 MPa
by Xiang Li, Xuewen Zhang, Tianya Zhang, Ce Ji, Peiyong Ni, Wanzhong Li, Yiqiang Pei, Zhijun Peng and Raouf Mobasheri
Sustainability 2024, 16(21), 9471; https://doi.org/10.3390/su16219471 - 31 Oct 2024
Viewed by 875
Abstract
Nowadays it has become particularly valuable to control the Particulate Matter (PM) emissions from the road transport sector, especially in vehicle powertrains with an Internal Combustion Engine (ICE). However, almost no publication has focused on a comparison of the microscopic characteristics of gasoline [...] Read more.
Nowadays it has become particularly valuable to control the Particulate Matter (PM) emissions from the road transport sector, especially in vehicle powertrains with an Internal Combustion Engine (ICE). However, almost no publication has focused on a comparison of the microscopic characteristics of gasoline and ethanol spray under injection pressure conditions of more than 30 MPa, except in the impingement process. By using a Phase Doppler Particles Analyser (PDPA) system, the microscopic characteristics of gasoline and ethanol spray from a Gasoline Direct Injection (GDI) injector under injection pressure (PI) up to 50 MPa was fully explored in this research. The experimental results demonstrate that under the same PI, the second peak of the probability (pd) curves of droplet normal velocity for gasoline is slightly higher than that of ethanol. Moreover, gasoline spray exceeds ethanol by about 5.4% regarding the average droplet tangential velocity at 50 mm of jet downstream. Compared to ethanol, the pd curve’s peak of droplet diameter at (0, 50) for gasoline is 1.3 percentage points higher on average, and the overall Sauter mean diameter of gasoline spray is slightly smaller. By increasing PI from 10 MPa to 50 MPa, pd of the regions of “100 ≤ Weber number (We) < 1000” and “We ≥ 1000” increases by about 23%, and the pd of large droplets over 20 μm shows a significant reduction. This research would provide novel insights into the deeper understanding of the comparison between gasoline and ethanol spray in microscopic characteristics under ultra-high PI. Additionally, this research would help provide a theoretical framework and practical strategies to reduce PM emissions from passenger vehicles, which would significantly contribute to the protection and sustainability of the environment. Full article
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<p>A schematic diagram of the experimental setup.</p>
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<p>The nozzle geometry and PDPA test points.</p>
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<p>The positive directions of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>N</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>T</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>p</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>N</mi> </mrow> </msub> </mrow> </semantics></math> at (0, 50) under <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math> of 10 MPa and 50 MPa.</p>
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<p>The average <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>N</mi> </mrow> </msub> </mrow> </semantics></math> at (0, 50) as <math display="inline"><semantics> <mrow> <mi>t</mi> </mrow> </semantics></math> progresses under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>The average <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mi>T</mi> </mrow> </msub> </mrow> </semantics></math> at 50 mm of jet downstream under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>S</mi> <mi>M</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> at (0, 50) as <math display="inline"><semantics> <mrow> <mi>t</mi> </mrow> </semantics></math> progresses under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>p</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> at (0, 50) under <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math> of 10 MPa and 20 MPa.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>p</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> at (0, 50) under <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math> of 30 MPa and 50 MPa.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>p</mi> </mrow> <mrow> <mi>d</mi> </mrow> </msub> </mrow> </semantics></math> of droplets at (0, 50) based on the classification of <math display="inline"><semantics> <mrow> <mi>W</mi> <mi>e</mi> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>S</mi> <mi>M</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> at (−16, 50) as <math display="inline"><semantics> <mrow> <mi>t</mi> </mrow> </semantics></math> progresses under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>S</mi> <mi>M</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> at (16, 50) as <math display="inline"><semantics> <mrow> <mi>t</mi> </mrow> </semantics></math> progresses under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>S</mi> <mi>M</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> at 50 mm of jet downstream under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>D</mi> </mrow> <mrow> <mi>S</mi> <mi>M</mi> <mi>D</mi> </mrow> </msub> </mrow> </semantics></math> at (0, 50), (0, 60) and (0, 70) under different <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mi>I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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24 pages, 9787 KiB  
Article
Impact of the Source Material Gradation on the Disaster Mechanism of Underground Debris Flows in Mines
by Rujun Tuo, Haiyong Cheng, Shunchuan Wu, Jiayang Zou, Deng Liu, Weihua Liu, Jing Zhang, Guanzhao Jiang and Wei Sun
Sustainability 2024, 16(20), 8788; https://doi.org/10.3390/su16208788 - 11 Oct 2024
Viewed by 802
Abstract
In mines where the natural caving method is used, the frequent occurrence of underground debris flows and the complex mine environments make it difficult to prevent and control underground debris flows. The source is one of the critical conditions for the formation of [...] Read more.
In mines where the natural caving method is used, the frequent occurrence of underground debris flows and the complex mine environments make it difficult to prevent and control underground debris flows. The source is one of the critical conditions for the formation of debris flows, and studying the impact of source material gradation on underground debris-flow disasters can effectively help prevent and control these occurrences. This paper describes a multiscale study of underground debris flows using physical model experiments and the discrete-element method (PFC3D) to understand the impact of the source material gradation on the disaster mechanism of underground debris flows from macroscopic and microscopic perspectives. Macroscopically, an increase in content of medium and large particles in the gradation will enhance the instantaneous destructive force. Large particles can more easily cause disasters than medium and fine particles with the same content, but the disaster-causing ability is minimized when the contents of medium and large particles exceed 50% and 60%, respectively. With increasing fine particle content, the long-distance disaster-causing ability and duration is increased. On the microscopic level, the source-level pairs affect the initial flow mode, concentration area of the force chain, average velocity, average runout distance, and change in energy of the underground debris flow. Among them, the proportion of large particles in the gradation significantly affects the change in kinetic energy, change in dissipative energy, time to reach the peak kinetic energy, and time of coincidence of dissipative energy and gravitational potential energy. The process of underground debris flow can be divided into a “sudden stage”, a “continuous impact stage”, and a “convergence and accumulation stage”. This work reveals the close relationship between source material gradation and the disaster mechanism of underground debris flows and highlights the necessity of considering the source material gradation in the prevention and control of underground debris flows. It can provide an important basic theory for the study of environmental and urban sustainable development. Full article
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<p>Experimental device: (<b>A</b>) on-site experimental equipment and (<b>B</b>) experimental model design drawing.</p>
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<p>Moraine materials of different particle sizes: (<b>a</b>) &lt;8 mm, (<b>c</b>) 8–20 mm, and (<b>c</b>) 20–40 mm.</p>
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<p>Particle size distribution (PSD) of the moraine samples: (<b>a</b>) particle size frequency curve and (<b>b</b>) particle size accumulation curve.</p>
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<p>Changes in vibration acceleration with time.</p>
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<p>Impact pressure–time relationship curves of G1–G6 in S1S2.</p>
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<p>Components of the linear model of the rolling resistance of the adhesive.</p>
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<p>Numerical simulation device and initial deposition of particles.</p>
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<p>Comparison of the model experiment and numerical simulation experiment results. Among them, (<b>a1</b>–<b>a5</b>) are the results of debris flow movement of physical experiments at five time points; the (<b>b1</b>–<b>b5</b>) are the results of the debris flow movement of the numerical experiment at five time points.</p>
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<p>Experimental and numerical simulation results of the final impact distance of the debris flow.</p>
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<p>Spatial distribution of the initial velocity of the particle column.</p>
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<p>Changes in the initial flow contact force chain of the particle column. Among them, (<b>a1</b>–<b>a3</b>), (<b>b1</b>–<b>b3</b>), (<b>c1</b>–<b>c3</b>), (<b>d1</b>–<b>d3</b>), (<b>e1</b>–<b>e3</b>) and (<b>f1</b>–<b>f3</b>) are the force chain structure of the initial movement of debris flow under the source gradation of 3:1:2, 5:1:2, 3:3:2, 3:5:2, 3:1:4 and 3:1:6 respectively.</p>
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<p>Motion characteristics of particles at different times.</p>
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<p>Changes in average velocity of underground debris flows with different source gradations over time.</p>
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<p>Changes in average runout distance of underground debris flows with time for different source gradations.</p>
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<p>The evolution characteristics of kinetic energy, potential energy, and loss energy with time when underground debris flow occurs in the original gradation, G1 (3:1:2); fine particle group, G2 (5:1:2); medium particle groups, G3 (3:3:2) and G4 (3:5:2); and large particle groups, G5 (3:1:4) and G6 (3:1:6).</p>
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18 pages, 5887 KiB  
Article
Research on the Vibration Response of High-Rise Buildings under Blasting Load
by Yubao Yuan, Zhenghua Gao, Lu He and Zhen Lei
Mathematics 2024, 12(20), 3165; https://doi.org/10.3390/math12203165 - 10 Oct 2024
Viewed by 712
Abstract
The vibration caused by blasting load may result in damage to high-rise buildings. In view of this consideration, an investigation of the vibration law was conducted in the context of an actual engineering project. The objective of this study was to analyze the [...] Read more.
The vibration caused by blasting load may result in damage to high-rise buildings. In view of this consideration, an investigation of the vibration law was conducted in the context of an actual engineering project. The objective of this study was to analyze the peak particle velocity (PPV), vibration frequency, and peak particle stress (PPS) of the buildings within a range of 50 m to 250 m from the epicenter, under the condition of a single-shot charge of 30 kg. To achieve this, a combination of theoretical analysis, field tests, and numerical experiments was employed. Sadovsky’s formula was used in combination with the least squares method to fit the propagation law of ground PPV. ANSYS 17.0/LS-DYNA and Origin 8.0 software were applied to study the amplification effect of building PPV and the relationship between PPV and PPS. Taking into account the difference between the height of the ground measuring point and the height of the explosive center, we investigated the PPV of high-rise buildings under three conditions of 36 m, 6 m, and −24 m drop from the explosive center, to strengthen the in-depth understanding of resonance effect. The following conclusions were reached: the ground PPV decreases with increasing horizontal distance from the explosive center, with the radial PPV being the largest. The vertical PPV of buildings exhibits a height amplification effect, with a magnification factor of 2.66. The radial and tangential PPVs of buildings demonstrate that the middle layer exhibits a relatively modest speed, whereas the low and high layers demonstrate considerably higher speeds. The greater the vertical distance from the explosion center is, the greater is the PPV. The vibration frequency is irregular, with an average of 10 Hz. The PPV of buildings is not proportional to the PPS, which is the highest at the bottom. It is recommended that the PPS of buildings be included in the criteria for safety allowances in blasting vibration. Full article
(This article belongs to the Special Issue Advances in Applied Mathematics, Mechanics and Engineering)
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<p>Blasting operation site. (<b>a</b>) High-rise buildings; (<b>b</b>) explosive area; (<b>c</b>) layout plan; (<b>d</b>) rock at the site.</p>
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<p>Vibration monitoring on site. (<b>a</b>) Monitoring points; (<b>b</b>) ground monitoring; (<b>c</b>) building monitoring. Vibrometers 1* to 5* were installed to monitor ground vibration, while vibrometers 1# to 5# were installed to monitor the buildings’ vibration.</p>
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<p>Propagation laws of PPV. Scatter plots of (<b>a</b>) radial, (<b>b</b>) vertical, and (<b>c</b>) tangential PPV changes with HDEC. Also shown are line charts of (<b>d</b>) radial, (<b>e</b>) vertical, and (<b>f</b>) tangential PPV changes with floor.</p>
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<p>Propagation laws of frequency. (<b>a</b>) Scatter plot of frequency changes with HDEC. Also shown are line charts of (<b>b</b>) radial, (<b>c</b>) vertical, and (<b>d</b>) tangential frequency changes with floor.</p>
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<p>Rock–High-rise Buildings model. (<b>a</b>) Elevation view; (<b>b</b>) 3D diagram.</p>
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<p>Propagation laws of PPV. (<b>a</b>) Line chart of PPV changes with HDEC. Also shown are line charts of (<b>b</b>) radial, (<b>c</b>) vertical, and (<b>d</b>) tangential PPV changes with floor.</p>
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<p>Rock-High-rise building models. (<b>a</b>) VDEC = −24 m; (<b>b</b>) VDEC = 6 m; (<b>c</b>) VDEC = 36 m; (<b>d</b>) velocity cloud map of tangential PPV.</p>
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<p>PPV. (<b>a</b>) Waveform of vertical PPV changes with time. Also shown are line charts of (<b>b</b>) radial, (<b>c</b>) vertical, and (<b>d</b>) tangential PPV changes with floor.</p>
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<p>PPV and PPS. (<b>a</b>) Stress waveform diagram. (<b>b</b>) Line chart of peak stress changes with floor. (<b>c</b>) Line chart of combined PPV changes with floor.</p>
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<p>Modal analysis of the high-rise building. (<b>a</b>) Model of high-rise building. (<b>b</b>–<b>k</b>) Step 1–10 modal analysis.</p>
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25 pages, 10539 KiB  
Article
Evaluation of Cumulative Damage and Safety of Large-Diameter Pipelines under Ultra-Small Clear Distance Multiple Blasting Using Non-Electric and Electronic Detonators
by Xiaoming Guan, Ning Yang, Yingkang Yao, Bocheng Xin and Qingqing Yu
Appl. Sci. 2024, 14(19), 9112; https://doi.org/10.3390/app14199112 - 9 Oct 2024
Viewed by 757
Abstract
The safety assessment and control of large-diameter pipelines under tunnel blasting at ultrasmall clear distances is a significant problem faced in construction. However, there has been no reference case for the quantitative comparison of the disturbance degree of surrounding rock by using two [...] Read more.
The safety assessment and control of large-diameter pipelines under tunnel blasting at ultrasmall clear distances is a significant problem faced in construction. However, there has been no reference case for the quantitative comparison of the disturbance degree of surrounding rock by using two blasting schemes of non-electric detonator design and electronic detonator design under a similar total blasting charge consumption. In this study, the blasting test was carried out based on the engineering background of drilling and blasting methods to excavate the tunnel under the water pipeline at a close distance. The peak particle velocity (PPV), stress, and deformation responses of the pipeline under the two construction methods of non-electric and electronic detonators were comparatively analyzed. The PPV can be remarkably reduced by 64.2% using the hole-by-hole initiation of the electronic detonators. For the large-diameter pipeline, the PPV on the blasting side was much larger than that on the opposite side because the blasting seismic wave propagated a longer distance and attenuated more rapidly, owing to its greater cavity vibration reduction effect. The PPV of the electronic detonators decayed more slowly than that of the non-electric detonators. The cumulative damage caused by consecutive hole-by-hole blasting using electronic detonators was less than that caused by simultaneous multi-hole initiation using non-electric detonators, with a reduction of about 50.5%. When the nearest peripheral holes away from the pipeline are detonated, the cumulative damage variable D and damage range increase rapidly. The PPV, dynamic tensile strength, and cumulative damage variables were used to evaluate the safety of the pipelines. Full article
(This article belongs to the Special Issue New Challenges in Urban Underground Engineering)
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<p>High-speed railway tunnel underneath an existing large water pipeline.</p>
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<p>Blast-hole layout of the upper bench.</p>
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<p>Design and implementation process of alternative in situ testing: (<b>a</b>) Diagram of the testing; (<b>b</b>) the operating process of testing.</p>
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<p>Vibration waveform monitored from tests. (<b>a</b>–<b>c</b>) correspond to the vibration velocity in the <span class="html-italic">x</span>, <span class="html-italic">y</span>, and <span class="html-italic">z</span> directions, respectively.</p>
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<p>Relationship of different strength parameters of JH-2 material model.</p>
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<p>Change stage of mechanical properties of materials under impact load of RHT model.</p>
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<p>Explosion stress wave pulse function curve.</p>
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<p>Numerical model. (<b>a</b>) Size parameters and (<b>b</b>) grid division.</p>
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<p>The comparison between in situ test results and calculated results. (<b>a</b>–<b>c</b>) are the comparison of the blasting vibration velocity extracted from the field monitoring and numerical simulation respectively.</p>
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<p>Damage and crack development of surrounding rock of upper bench after the detonation of each part using non-electric detonators: (<b>a</b>) Cut holes H1 detonation; (<b>b</b>) relief holes H2 detonation; (<b>c</b>) relief holes H3 detonation; (<b>d</b>) peripheral holes H4 detonation; (<b>e</b>) bottom holes H5 detonation.</p>
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<p>The (<b>c</b>) of the dangerous point of the pipeline using non-electric detonator blasting: (<b>a</b>), (<b>b</b>–<b>d</b>) are the PPV of <span class="html-italic">x</span>-, <span class="html-italic">y</span>-, <span class="html-italic">z</span>-direction and integrated PPV, respectively.</p>
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<p>The (<b>c</b>) of the dangerous point of the pipeline using non-electric detonator blasting: (<b>a</b>), (<b>b</b>–<b>d</b>) are the PPV of <span class="html-italic">x</span>-, <span class="html-italic">y</span>-, <span class="html-italic">z</span>-direction and integrated PPV, respectively.</p>
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<p>Layout of blast holes using electronic detonators.</p>
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<p>PPV of the dangerous point of the pipeline using electronic detonator blasting: (<b>a</b>–<b>d</b>) are the PPV of <span class="html-italic">x</span>-, <span class="html-italic">y</span>-, <span class="html-italic">z</span>-direction and integrated PPV, respectively.</p>
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<p>The vibration response of the extracted elements at the bottom of the pipeline. (<b>a</b>–<b>c</b>) are <span class="html-italic">x-</span>, <span class="html-italic">y-</span>and <span class="html-italic">z-</span>directions.</p>
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<p>The vibration response of the extracted elements at the closest profile of the pipeline. (<b>a</b>–<b>c</b>) are <span class="html-italic">x</span>-, <span class="html-italic">y</span>-and <span class="html-italic">z</span>-directions.</p>
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<p>Distributions of PTS and displacement on the cross-section of the pipeline using the two blasting schemes. (<b>a</b>) PTS; (<b>b</b>) displacement.</p>
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<p>Evolution of cumulative damage in the original blasting scheme (<b>a</b>–<b>e</b>) and the improved blasting scheme (<b>a′</b>–<b>e’</b>) after comparing the five stages of blasting.</p>
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<p>Relationship between the cumulative damage degree of pipeline and the number of blast hole detonations.</p>
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<p>Design of blast holes and damping holes in the upper bench.</p>
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<p>Field monitoring verifies the optimization results. (<b>a</b>) Monitoring point location. (<b>b</b>) Variation in the maximum PPV in the whole process of excavation.</p>
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25 pages, 12952 KiB  
Article
Numerical Simulation of a Shed-Tunnel Structure’s Dynamic Response to Repeated Rockfall Impacts Using the Finite Element–Smoothed Particle Hydrodynamics Method
by Hao Zhao, Zepeng Lyu and Hongyan Liu
Buildings 2024, 14(10), 3143; https://doi.org/10.3390/buildings14103143 - 2 Oct 2024
Viewed by 520
Abstract
In practical engineering, a shed-tunnel structure often encounters repeated impacts from rockfall during its whole service life; therefore, this research focuses on exploring the dynamic response characteristics of shed-tunnel structures under repeated impacts from rockfall with a numerical method. First of all, based [...] Read more.
In practical engineering, a shed-tunnel structure often encounters repeated impacts from rockfall during its whole service life; therefore, this research focuses on exploring the dynamic response characteristics of shed-tunnel structures under repeated impacts from rockfall with a numerical method. First of all, based on a model test of a shed tunnel under rockfall impacts as a reference, an FEM (finite element method)-SPH (Smoothed Particle Hydrodynamics) coupled numerical calculation model is established based on the ANSYS/LS-DYNA finite element code. Numerical simulation of the dynamic response of the shed-tunnel structure under rockfall impacts is realized, and the rationality of the model is verified. Then, with this model and the full restart technology of the LS-DYNA code, the effects of four factors, e.g., rockfall mass, rockfall impact velocity, rockfall impact angle and rockfall shape, on the impact force and impact depth of the buffer layer, the maximum plastic strain and axial force of the rebar, the shed roof’s vertical displacement and plastic strain of the shed tunnel are studied. The results show that the impact force, impact depth, roof displacement and plastic strain of the shed tunnel are positively correlated with the rockfall mass, velocity and angle under multiple rockfall impacts. The impact force, roof displacement and plastic strain of the shed-tunnel structure generated by the impact of rockfall consisting of cuboids are all greater than those under spherical rockfall, and the impact depth generated by the impact of spherical rockfall is greater than that of rockfall consisting of cuboids. For rockfall consisting of cuboids, the impact depth, roof displacement and plastic strain are negatively correlated with the contact area. Under repeated rockfall impacts, the peak impact force usually increases first and then tends to be stable. Full article
(This article belongs to the Section Building Structures)
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<p>The coupled FEM-SPH numerical calculation model and the bars for the reinforced concrete. (<b>a</b>) The numerical calculation model; (<b>b</b>) two layers of the reinforcing rebar.</p>
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<p>Comparison of impact force calculation results obtained with six methods, e.g., Japan Road Association’s method [<a href="#B35-buildings-14-03143" class="html-bibr">35</a>], Yang and Guan’s method [<a href="#B36-buildings-14-03143" class="html-bibr">36</a>], Switzerland’s method [<a href="#B37-buildings-14-03143" class="html-bibr">37</a>], the tunnel manual’s method [<a href="#B38-buildings-14-03143" class="html-bibr">38</a>] and test results [<a href="#B17-buildings-14-03143" class="html-bibr">17</a>].</p>
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<p>Comparison of the simulation results and test ones of the mid-span bending main crack initiation, propagation and coalescence. (<b>a</b>) Crack initiation and propagation. (<b>b</b>) Crack coalescence.</p>
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<p>The workflow of this study.</p>
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<p>The time–history curve of the impact force on the buffer layer with different rockfall masses.</p>
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<p>The time–history curve of the impact depth in the buffer layer with different rockfall mass.</p>
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<p>The time–history curve of the maximum plastic strain of the rebar with different rockfall mass.</p>
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<p>The time–history curve of the vertical displacement of the shed roof with different rockfall masses.</p>
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<p>Effect of the rebar on the vertical displacement of the shed roof.</p>
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<p>The maximum axial force of the rebar with different rockfall masses.</p>
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<p>The plastic strain contour of the shed tunnel with different rockfall masses. (<b>a</b>) m = 70.3 kg and after five impacts (<b>b</b>) m = 137.31 kg and after five impacts (<b>c</b>) m = 237.26 kg and after four impacts.</p>
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<p>The time–history curve of the impact force on the buffer layer with different rockfall impact velocity.</p>
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<p>The time–history curve of the impact depth in the buffer layer with different rockfall impact velocities.</p>
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<p>The time–history curve of the rebar maximum plastic strain with different rockfall impact velocities.</p>
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<p>The time–history curve of the vertical displacement of the shed roof with different rockfall impact velocities.</p>
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<p>The maximum axial force of the rebar with different rockfall impact velocities.</p>
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<p>The plastic strain contour of the shed tunnel with the rockfall impact velocity. (<b>a</b>) <span class="html-italic">v</span> = 15 m/s and after five impacts (<b>b</b>) <span class="html-italic">v</span> = 20 m/s and after five impacts (<b>c</b>) <span class="html-italic">v</span> = 25 m/s and after four impacts.</p>
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<p>The time–history curve of the impact force on the buffer layer with different rockfall shapes.</p>
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<p>The time–history curve of the impact depth in the buffer layer with different rockfall shapes.</p>
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<p>The time–history curve of the maximum plastic strain of the rebar with different rockfall shapes.</p>
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<p>The time–history curve of the vertical displacement of the shed roof with different rockfall shapes.</p>
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<p>The maximum axial force of the rebar with different rockfall shapes.</p>
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<p>The plastic strain contour of the shed tunnel with the rockfall shape. (<b>a</b>) Sphere and after five impacts; (<b>b</b>) square 1 and after five impacts; (<b>c</b>) square 2 and after four impacts.</p>
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<p>The time–history curve of the impact force on the buffer layer with different rockfall impact angles.</p>
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<p>The time–history curve of the impact depth in the buffer layer with different rockfall impact angles.</p>
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<p>The time–history curve of the maximum plastic strain of the rebar with different rockfall impact angles.</p>
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<p>The time–history curve of the vertical displacement of the shed roof with different rockfall impact angles.</p>
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<p>The maximum axial force of the rebar with different rockfall impact angles.</p>
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<p>The plastic strain contour of the shed-tunnel with the rockfall impact angle after five impacts. (<b>a</b>) <span class="html-italic">θ</span> = 30° (<b>b</b>) <span class="html-italic">θ</span> = 45° (<b>c</b>) θ = 60° (<b>d</b>) <span class="html-italic">θ</span> = 75° (<b>e</b>) <span class="html-italic">θ</span> = 90°.</p>
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16 pages, 8291 KiB  
Article
Mechanical Properties and Tribological Study of Bottom Pouring Stir-Cast A356 Alloy Reinforced with Graphite Solid Lubricant Extracted from Corn Stover
by Vavilada Satya Swamy Venkatesh and Pandu Ranga Vundavilli
Lubricants 2024, 12(10), 341; https://doi.org/10.3390/lubricants12100341 - 2 Oct 2024
Viewed by 808
Abstract
The present work epitomises extracting the graphite (Gr) solid lubricant from the corn stover. The extracted Gr was incorporated as reinforcement in the A356 alloy (Al-7Si), and the effect of the Gr particles on the mechanical and tribological properties was investigated. In spite [...] Read more.
The present work epitomises extracting the graphite (Gr) solid lubricant from the corn stover. The extracted Gr was incorporated as reinforcement in the A356 alloy (Al-7Si), and the effect of the Gr particles on the mechanical and tribological properties was investigated. In spite of this, the input process parameters for the dry sliding wear test at room temperature against the EN31 steel disc were optimised through ANOVA analysis. The fabricated A359—X wt% (X = 0, 2.5, 5, 7.5) composite through bottom pouring stir casting techniques was analysed microstructurally by using XRD and FESEM analysis. The micro Brinell hardness and tensile strength were investigated per ASTME10 and ASTME8M standards. A wear test was performed for the composite pins against the EN31 steel disc according to ASTM G99 specifications. The XRD analysis results depict the presence of carbon (C), aluminium (Al), and silicon (Si) in all the wt% of the Gr reinforcement. However, along with the elements, the Al2Mg peak was confirmed for the A356—7.5 wt% Gr composite and the corresponding cluster element was confirmed in FESEM analysis. The maximum micro Brinell hardness of 92 BHN and U.T.S of 123 MPa and % elongation of 7.11 was attained at 5 wt% Gr reinforcement due to uniform Gr dispersion in the A356 alloy. Based on the ANOVA analysis, the optimal process parameters were obtained at 20 N applied load, 1 m/s sliding velocity, and 1000 m sliding distance for the optimal wear rate of 0.0052386 g/km and 0.364 COF. Full article
(This article belongs to the Special Issue Tribology for Lightweighting)
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<p>(<b>a</b>,<b>b</b>) FESEM and EDX spectra for Gr particles, and (<b>c</b>,<b>d</b>) FESEM and EDX for A356 alloy.</p>
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<p>(<b>a</b>,<b>b</b>) FESEM and EDX spectra for Gr particles, and (<b>c</b>,<b>d</b>) FESEM and EDX for A356 alloy.</p>
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<p>(<b>a</b>) Bottom pouring stir casting setup. (<b>b</b>) Fabricated tensile test specimens.</p>
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<p>Optical microscope images for the (<b>a</b>) A359—2.5 wt% Gr, (<b>b</b>) A359—5 wt% Gr, and (<b>c</b>) A359—7.5 wt% Gr composites.</p>
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<p>XRD pattern for the A356, C1, C2, and C3 composites.</p>
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<p>FESEM and EDS spectra for the (<b>a</b>,<b>b</b>) A356—2.5 wt% Gr and (<b>c</b>,<b>d</b>) A356-5 wt% Gr composites.</p>
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<p>FESEM and EDX for the clusters in the A356—7.5 wt% Gr composite.</p>
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<p>Hardness of the cast composites.</p>
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<p>U.T.S and % elongation of the cast composites.</p>
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<p>(<b>a</b>) Wear track for the tribology test and (<b>b</b>) fabricated composite pins.</p>
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<p>Variation in (<b>a</b>) COF and (<b>b</b>) wear rate for the cast composites.</p>
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<p>SEM micrographs for the worn surface at 1000 m sliding distance and 40 N applied load (<b>a</b>) sliding direction (<b>b</b>) Delamination wear (<b>c</b>,<b>d</b>) Fine grooves.</p>
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<p>Actual and predicted values for the (<b>a</b>) wear rate and (<b>b</b>) COF.</p>
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<p>Residue vs. run for (<b>a</b>) COF and (<b>b</b>) wear rate.</p>
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<p>Effect of input process parameters on COF.</p>
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<p>Effect of input process parameters on COF.</p>
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<p>Effect of input process parameters on the wear rate.</p>
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28 pages, 17742 KiB  
Article
Vibration Safety Threshold and Control Technology for Blasting to Prevent Seawater Intrusion in Coastal Tunnel Sections Near Faults
by Xiaodong Wu, Xiaomeng Miao, Min Gong, Junpeng Su, Yaqi Zhu and Xiaolei Chen
J. Mar. Sci. Eng. 2024, 12(9), 1646; https://doi.org/10.3390/jmse12091646 - 14 Sep 2024
Cited by 1 | Viewed by 660
Abstract
Coastal underground engineering projects are prone to seawater intrusion during blasting operations, posing significant risks to the safety of construction personnel and the structural integrity of the projects. To ensure the safety of blasting operations in areas at risk of seawater intrusion, this [...] Read more.
Coastal underground engineering projects are prone to seawater intrusion during blasting operations, posing significant risks to the safety of construction personnel and the structural integrity of the projects. To ensure the safety of blasting operations in areas at risk of seawater intrusion, this study focuses on a section of a coastal tunnel that is at risk of such intrusion. Using fracture mechanics theory and silo theory analysis methods, the minimum safe distance between the workface and the fault to prevent seawater intrusion is determined. Numerical simulations are employed to analyze the dynamic response of the surrounding rock and the attenuation of vibrations as blasting excavation progresses near the fault-controlled zone. This study also explores the impact of dynamic excavation on fault stability. By employing a regression analysis, this study establishes quantitative relationships between the amount of explosive used and the peak particle velocity (PPV) at different distances, as well as between the range of rock damage and PPV at various distances. This analysis allows for the determination of a safe PPV threshold to prevent seawater intrusion in the fault-controlled area. The accuracy of the computational model is validated using field-measured data. Finally, an optimized blasting design and strategy based on electronic detonator initiation are proposed for the control area, ensuring construction safety. This study provides theoretical and technical references for achieving safe and efficient blasting excavation in coastal underground engineering projects. Full article
(This article belongs to the Section Coastal Engineering)
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<p>Schematic diagram of topography and geology of transportation tunnel. (<b>a</b>) Faults, jointed zones, and surrounding marine environment in tunnel excavation region. (<b>b</b>) Stratigraphic structure of transportation tunnel.</p>
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<p>Drawing of transportation tunnel section design (unit: m).</p>
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<p>Conventional blasting scheme for transportation tunnel (unit: cm).</p>
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<p>Schematic diagram of tunnel excavation near faults. (<b>a</b>) Stratigraphic structure of the tunnel. The stratigraphic information is the same as in <a href="#jmse-12-01646-f001" class="html-fig">Figure 1</a>b. (<b>b</b>) Computational model.</p>
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<p>A schematic diagram of the seawater intrusion risk control zone under conventional blasting.</p>
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<p>Three-dimensional solid model.</p>
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<p>A schematic diagram of the rock fragmentation due to blast loading.</p>
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<p>Schematic diagram of equivalent boundary for different blastholes: (<b>a</b>) cut holes, (<b>b</b>) easer holes, and (<b>c</b>) contour holes.</p>
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<p>The time history curves of the EBL for each segment of the blastholes under the conventional blasting scheme.</p>
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<p>Blasting vibration monitoring. (<b>a</b>) Schematic diagram of location of measurement points in numerical simulation model. (<b>b</b>) Vibration measured on site.</p>
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<p>Comparison of simulated and measured vibration waveforms at measurement point 1. (<b>a</b>) X-direction velocity; (<b>b</b>) Y-direction velocity; (<b>c</b>) Z-direction velocity; (<b>d</b>) resultant velocity.</p>
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<p>Comparison of simulated and measured vibration waveforms at measurement point 1. (<b>a</b>) X-direction velocity; (<b>b</b>) Y-direction velocity; (<b>c</b>) Z-direction velocity; (<b>d</b>) resultant velocity.</p>
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<p>Model of blasting excavation near F10 fault with different blasting charges.</p>
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<p>The specific layout of the measurement points.</p>
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<p>PPV at various measuring points under different explosive charge conditions. (<b>a</b>) Z-direction velocity. (<b>b</b>) Resultant velocity.</p>
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<p>PPV curves for each measurement point. (<b>a</b>) Z-direction velocity. (<b>b</b>) Resultant velocity.</p>
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<p>Attenuation patterns of PPV at each measurement point. (<b>a</b>) Z-direction velocity. (<b>b</b>) Resultant velocity.</p>
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<p>Surrounding rock damage cloud diagrams for Models I to VI. (<b>a</b>) Z-direction velocity; (<b>b</b>) resultant velocity. (<b>a</b>) <span class="html-italic">Q<sub>m</sub></span> = 45 kg; (<b>b</b>) <span class="html-italic">Q<sub>m</sub></span> = 47 kg; (<b>c</b>) <span class="html-italic">Q<sub>m</sub></span> = 49 kg; (<b>d</b>) <span class="html-italic">Q<sub>m</sub></span> = 51 kg; (<b>e</b>) <span class="html-italic">Q<sub>m</sub></span> = 53 kg; (<b>f</b>) <span class="html-italic">Q<sub>m</sub></span> = 55 kg.</p>
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<p>Relationship between <span class="html-italic">D<sub>s</sub></span> and <span class="html-italic">Q<sub>m</sub></span>.</p>
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<p>Linear regression fit results for relationship between surrounding rock’s damage range and PPV.</p>
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<p>The design process for control basting in fault-adjacent sections.</p>
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<p>Calculation flow chart of time parameters for electronic detonator.</p>
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<p>Optimized blasting plan.</p>
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<p>Measured blast vibration waveform at 30 m from workface. (<b>a</b>) X-direction; (<b>b</b>) Y-direction; (<b>c</b>) Z-direction; (<b>d</b>) resultant velocity.</p>
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<p>Measured blast vibration waveform at 30 m from workface. (<b>a</b>) X-direction; (<b>b</b>) Y-direction; (<b>c</b>) Z-direction; (<b>d</b>) resultant velocity.</p>
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