Abstract: With the depletion of the earth’s shallow resources, the exploration of deep rock engineering has become a research hotspot. The research mostly focuses on the influence of high temperature on the properties of deep rocks. This study aims to understand the thermal damage evolution mechanism in a rock under high temperature and make a reasonable evaluation on the safety and stability of underground rock engineering, such as ultra-deep well drilling, deep ground laboratory, nuclear waste disposal, and geothermal resource development. Based on the analysis and review of domestic and foreign literature, the authors systematically reviewed the research progress and development of deformation and failure of the high-temperature rock masses and temperature-varying rock masses under temperature effect. The physical and mechanical properties of rocks after being subjected to high temperature and under real-time high temperature were briefly described. The changes with temperature in the physical and mechanical parameters of deep rocks were summarized. The latest research on the deformation and failure mechanism under high temperature was analyzed, and the applications of advanced auxiliary test technologies, such as acoustic emission (AE), ultrasonic testing (UT), X-ray diffraction (XRD), polarizing microscope (PM), scanning electron microscope (SEM), nuclear magnetic resonance (NMR), and computed tomography (CT) scanning system, in the deformation and failure analysis were introduced. The advantages and disadvantages of the coupled thermal-stress model of the rock, the numerical analysis method, and the applicable conditions were summarized. The variation characteristics of the rock’s mechanical parameters under high temperature were briefly described. Finally, the limitations of the current studies on high-temperature thermal damage in deep rocks were pointed out. The future prospects were discussed from several aspects, i.e., to explore the mechanism of rock thermal damage in a multi-scale and multi-field-phase, and the evolution law of rock thermal damage was systematically analyzed from macro, meso, and micro aspects.
Abstract: Whether domestic or foreign, the utilization of phosphogypsum (PG) resources is not satisfactory. A chemical plant in Guizhou produces phosphoric acid through a semi-aqueous process to obtain the byproduct hemihydrate phosphogypsum (HPG), which has a certain gelling activity. If this feature of HPG can be fully utilized, it can replace cement as a cementing material to prepare mine-filling materials. Utilizing HPG for goaf filling can not only reduce the environmental protection problems caused by the surface discharge of PG but also eliminate the hidden safety hazards in the goaf. At present, when HPG is used to prepare mine-filling cementitious materials, HPG will be consolidated into a block and lose its gelling activity when it is stacked for a certain period of time. The gelling performance of the HPG in the storage state appears to decline. Based on the indoor HPG crystal water detection and uniaxial compression test and setting four different storage temperatures (20 ℃, 40 ℃, 60 ℃, and 80 ℃), this study explored the changes in the mass fraction of the crystal water of HPG samples under different storage temperatures. The compressive strength development law of HCM prepared after storage and microscopic analysis methods, such as scanning electron microscopy, were used to study the influence mechanism of the storage temperature on its strength. Results show that the stacking temperature has a significant effect on the gelling performance of HPG. A high stacking temperature will speed up the conversion of free water in the HPG sample to crystal water and inhibit the strength development of the HCM prepared after stacking. Data standardization was used to predict the compressive strength of samples after storage at different temperatures, which is confirmed to be in good agreement with the measured values. The microscopic analysis found that the storage temperature mainly affects the supersaturation of the system, and the microscopic morphology of the HCM prepared after storage at different temperatures is different.
Abstract: With the development of the steel industry, the use of high-grade and easy-to-handle iron ore is gradually decreasing. At present, the effective utilization of low-grade and refractory iron ore, particularly high-phosphorus oolitic iron ore, has gradually become a research hotspot and a worldwide problem. This type of ore is mainly distributed in the USA, France, Germany, Russia, and China and often has an oolitic structure, where the intercalation relationship between iron minerals and gangue minerals is complicated and the phosphorus content is high. Therefore, this type of ore has not yet been developed and utilized. Studies have shown that the use of coal-based direct reduction–magnetic separation to process high-phosphorus oolitic iron ore is one of the methods to achieve efficient utilization of its iron resources. Researchers have conducted in-depth studies on process optimization, dephosphorization mechanism, and iron and phosphorus reduction kinetics. To determine the parameters for the industrial test of the rotary kiln, based on the best result of the small-scale test, a pilot-scale experiment on iron recovery and dephosphorization from high-phosphorus oolitic iron ore was conducted using coal-based direct reduction, followed by magnetic separation. Results showed that under the optimum conditions, the grade and recovery of iron and phosphorus contents in the powdered reduced iron concentrate were 94.17%, 77.47%, and 0.08%, respectively. Limestone dosage of 28%, anthracite dosage of 16%, reduction temperature of 1300 °C and reduction time of 3 h were recommended as the initial conditions for the industrial test of the rotary kiln. The mechanisms of anthracite were investigated by X-ray diffraction and scanning electron microscopy–energy-dispersive X-ray spectroscopy. The results showed that with the increase in anthracite dosage, the reduction of wustite and pleonaste and the growth of iron particles are promoted, thereby improving the recovery effect of iron. However, a high anthracite dosage enhanced the reducing atmosphere and its ash content consumed limestone, causing phosphorus in iron minerals and apatite to be reduced to elemental phosphorus and iron particles to form the iron–phosphorus alloy.
Abstract: Exhausted shallow resources have turned mining into deep mining, with the mining depth of most mines under construction being more than 1000 m. With the continuous increase of the mining depth of mineral resources, the thickness and strength grade of the shaft lining concrete increases, resulting in higher hydration heat. The freezing method is usually used in deep well construction, resulting in a high temperature on one side and a low temperature on the other side of the shaft wall concrete. The influence law of this environment on concrete needs to be studied. It is of great theoretical significance for deep well construction and service safety to find out the change law of the shaft wall concrete performance under a freezing construction environment. The temperature difference between ?5/60 ℃ and ?5/70 ℃ was applied to simulate the state of the mass concrete in the freezing method construction environment. The ultrasonic parameters, compressive strength, splitting tensile strength, chloride diffusion coefficient, and bursting liability of concrete under the simulated environment were studied, and the scanning electron microscope of the concrete was analyzed. Results show that the freezing construction environment will cause certain damage to the interior of the concrete, and the damage parallel to the heating direction is greater than that in the vertical direction. The damage of the C50 concrete is greater than that of the C70 concrete, and the temperature gradient will aggravate the internal damage of the concrete. The simulated freezing environment will have adverse effects on the compressive strength, splitting tensile strength, chloride ion permeability, and bursting liability of the concrete. The temperature difference has a positive correlation with the performance reduction rate, which becomes more significant for low-strength concrete. The internal microstructure of the concrete block is uneven due to the simulated freezing environment, the concrete structure at the low-temperature end is loose, and the structure at the high-temperature end is dense, resulting in the decrease of the concrete’s performance.
Abstract: Aiming at the research problems on rockbursts in the forefront of deep rock mass engineering science, the challenges restricting its quantitative dynamics and intelligent warning research were analyzed. The development mechanism of rockbursts and rockburst intelligent monitoring and warning are the key technical issues for the safe construction of deep rock mass engineering. In this study, a rockburst database management system was established to accurately and effectively collect the characteristics of rockbursts and their corresponding geological as well as excavation information, fracture response monitoring, and other information in different stages of the project. On this basis, the differences and connections between different projects were constructed to study the rockburst mechanism and intelligent monitoring and warning of rockbursts as a whole. Accordingly, the problems of lack of sample numbers and unbalanced sample structure of rockburst cases of different types and intensities were effectively solved. Object-oriented B/S + C/S structure was adopted, and the rockburst database management system was established to break through the constraints of challenges. This rockburst database management system includes a rockburst case database, microseismic waveform database, and microseismic time sequence database and has the functions of multi-engineering management, detailed data acquisition, query analysis, and result export. The detailed collection and effective management of multi-engineering and multi-source rockburst disaster information were successfully realized using the database management system. Several deep-buried rock mass projects with the rockburst disaster were used to apply the rockburst database management system. The three challenges of the rockburst mechanism and rockburst intelligent monitoring as well as warning were verified by examples, and satisfactory results were obtained. The results show that the rockburst database management system established in this study has good applicability, can be adapted to the needs of different stages of the project, and can also provide scientific and reliable data basis and reference for rockburst analogy and intelligent warning research in different projects.
Abstract: As an important way to obtain mineral resources, open-pit mining has accounted for about 77% of the total production of the mined iron ore, and about 52% of the total production of non-ferrous ore, indicating huge development potential. With the continuous development of open-pit mines to deep and large-scale directions, the height of mine slopes is constantly increasing and the maximum height has exceeded kilometers. Slope instability disaster is a major problem faced by open-pit mines, and the evaluation and analysis of the stability of mine slopes are of great importance. However, in the stability evaluation and analysis of rock slopes in many open-pit mines, the engineering scale is ignored, the value of design safety factor is too conservative, and the evaluation index is single, rendering it difficult to consider the economy and safety of mine slope evaluation and resulting in the waste of resources and frequent accidents. In this paper, rock slopes were divided into three scales according to the production process characteristics of open-pit mines: (1) overall slope, (2) inter-ramp slope, and (3) bench slope. Moreover, the control elements and failure modes of the slopes were analyzed. Combined with the design safety factor value of the civil-engineering slope standards and specifications of a non-coal open-pit mine slope, the design safety factor requirements of non-coal open-pit mine slopes at home and abroad were discussed, then six suggestions were put forward. Comprehensively taking service years and the improved scheme of design safety factor in slope scale into consideration, the instability probability were introduced to extend the design standard of slope stability evaluation in different scales, which can effectively improve the rationality and scientificity of the rock slope stability evaluation in non-coal open-pit mines, further improving the mining slope design theory and method.
Abstract: Given the widespread application of the lime precipitation process for arsenic removal in the smelting of arsenic-containing minerals, the resourcefulness of calcium arsenate use has received increasing attention. In general, more types of arsenate have different high-temperature characteristics, and the slag type is complicated under mixed reduction roasting and difficult to recover. Additionally, arsenate in the form of calcium arsenate is a more common and inexpensive product in the metallurgical process. Because whether it is arsenic-containing wastewater, arsenic slag, arsenate, and so on, the material can be separated from the system by inexpensive lime precipitation or calcification transformation in simple metallurgical equipment to generate calcium arsenate. Therefore, this paper was devoted to preparing commercially valuable metallic monomers of arsenic by carbon thermal roasting reduction of calcium arsenate and to starting scientific research to advance the harmless treatment of arsenic hazardous waste to arsenic resource recovery and use. Among them, thermogravimetric analysis shows that the mass loss of calcium arsenate mixed with carbon powder pyrolysis is divided into 3 stages: stages 1 and 2 are water loss processes, and stage 3 involves the carbon reduction of calcium arsenate to generate CaO and arsenic vapor. It is found that the stage III reaction mechanism could be explained using the phase boundary reaction kinetic model. The experimental results of single-factor conditions show that the arsenic volatilization rate reaches 99.94% at a constant temperature of 1000 °C for 60 min and a carbon allotment factor of 1.4. The characterization of the relevant products in the reaction system by X-ray diffractometer (XRD) and scanning electron microscope energy spectrometer (SEM?EDS) show that the arsenic product is mainly flaked metallic arsenic and amorphous powdered arsenicunder better conditions, and the roasted residue is CaO.
Abstract: Iron-ore tailings (IOT) are mineral waste obtained via the iron-ore mining process. This has become a very critical issue in industrial solid waste management. The stacking of IOT occupies a large area and causes serious pollution, which can harm human life. This has become a serious matter of concern for society. IOT are usually rich in SiO2 and Al2O3 and can be used as raw materials in producing zeolitic materials. They have substantial benefits from both economic and environmental perspectives. However, few studies have been reported on the synthesis of zeolite or zeolite-like materials using IOT. As a type of zeolite, ZSM-5 has a regular pore structure and high thermal and hydrothermal stability and is widely used in catalytic materials. However, the application of ZSM-5 is greatly limited in many catalytic reactions owing to the large molecules associated with its inherently small pore sizes (<1.5 nm). Introduction of a hierarchically porous structure into conventional ZSM-5 maintains the crystal structure, acidic active center, and high thermal and hydrothermal stability and accelerates the diffusion/transfer of large molecules and greatly reduces the formation of carbon residue. This prolongs the service life of the catalyst used, which is extremely desirable in catalysis. In this study, hierarchically porous ZSM-5 was prepared via a two-step process using IOT as a silica source instead of pure chemical reagents. First, mesoporous MCM-41 was synthesized using cetyltrimethylammonium bromide as a mesoporous template. Then, hierarchically porous ZSM-5 was fabricated by impregnating a structure-directing agent into the as-synthesized MCM-41, followed by a solid-phase conversion method to transform amorphous silica into a zeolite crystal. To evaluate the textural properties of the zeolites, the as-synthesized samples were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and nitrogen adsorption. The results show that phase separation between the surfactant and zeolite crystals is avoided because of the absence of the liquid-water phase during the solid-phase conversion. Therefore, the synthetic route presented herein provides a novel method for the synthesis of hierarchically porous ZSM-5 from IOT.
Abstract: Metal magnetic memory detection technology has been widely studied because it can identify damage to ferromagnetic components quickly and conveniently, and it is considered to have the ability to identify hidden damage. To promote the application of metal magnetic memory technology in the damage detection of a bridge steel box beam, a static bending test on the steel box beam of the bridge was performed, and the magnetic signal distribution of the upper flange with the most severe deformation was extracted. The quantitative relationship between the stress in the damaged region and magnetic signal or magnetic signal gradient was established, and an approach for characterizing the stress and damage state of the steel beam was proposed using the magnetic field gradient index. The results show that the magnetic signal curve of the upper flange is opposite to that of the stress change form, and the magnetic signal curve reverses to a negative value after entering the plastic state and increases with the stress change speed, so the component can be judged to enter the plastic state and soon be damaged. The maximum value of the magnetic field gradient curve appears in the position with the most severe damage, and with the increase in the load, the maximum value point of the magnetic gradient constantly moves to the middle of the steel beam; thus the early warning of the failure state can be conducted. The relationship curve between the magnetic field gradient and stress can obviously distinguish the entire stress process of the component, which includes four states: initial, yield, plasticity, and damage. The stress state and damage state of components can be characterized using the magnetic field gradient index. This study can provide a reference and basis for the application of metal magnetic memory detection technology in the quantitative assessment and early warning of the damage status of bridge steel box beams.
Abstract: As submarine oil and gas are exploited further, the safety of submarine pipelines is receiving increasing attention. Due to the complex operating environment and harsh working environment, submarine pipelines are vulnerable to damage; this leads to accidents. Once an accident occurs in the submarine pipeline, it not only causes massive economic losses but also adversely affects marine ecology. The metal magnetic memory (MMM) technology was proposed in the 20th century to detect macro defects and hidden defects early. To overcome the difficulties of the MMM quantitative inversion of submarine pipeline defects, this study proposed a gated recurrent unit (GRU) neural network model based on improved particle swarm optimization (IPSO). The X52 pipe specimens with blind plates that were welded at both ends were used, pipes had prefabricated defects of different diameters and depths. An 11-6W noncontact probe was used for underwater testing; the host was the TSC-5M-32 MMM Instrument. After conducting simulated submarine tests to obtain the MMM signals of pipe defects, the characteristic parameters of MMM signals with different defect sizes were extracted. It is found that the MMM characteristic parameters exhibit a complex nonlinear variation for different defect dimensions. Exploiting the GRU’s dual-gate structure that can remember the signal characteristics of defects and its superior nonlinear regression fitting ability, a quantitative MMM GRU inversion model was established for detecting submarine pipeline defects. Furthermore, considering the randomness of the hyper-parameter selection in the model, the IPSO algorithm was used to optimize the hyper-parameters. Validation results show that the model has an average accuracy of up to 96% and 93% for defect depth inversion and defect diameter inversion, respectively. Using the MMM method, this study provides a new idea and method for the quantitative identification and defect inversion of submarine pipeline defects.
Abstract: Person re-identification is an important part of multi-target tracking across cameras; its aim is to identify the same person across different cameras. Given a query image, the purpose of person re-identification is to find the best match for the query image in an image set. Person re-identification is a key component in an intelligent security system; it is beneficial for building a smart bank or smart factory and plays a crucial role in the construction of a smart city. Nowadays, with the development of artificial intelligence and increasing demand for precise identification in practical scenarios, deep learning-based person re-identification technology has become a popular research topic; this technology has achieved state-of-the-art results in comparison with conventional approaches. Although there are many recently proposed networks with stronger representation ability and a high level of accuracy for person re-identification, there also exist some problems that should be considered and solved. These include the insufficient generalization ability of various poses, the inability to fully utilize the temporal information, and the ineffective identification of occluded objects. As a result, many scholars have researched this field and have pointed out some promising solutions to cope with the aforementioned problems. This paper aims to summarize the application of deep learning in the field of person re-identification along with its advantages and shortcomings. First, the background of person re-identification is introduced, including the application scenarios, datasets, and evaluation indicators. Additionally, some basic methods of person re-identification based on deep learning are summarized. According to the existing research on person re-identification, the main approaches proposed by scholars worldwide can be summarized into four aspects, which are based on local features, generative adversarial networks, video data, and re-ranking. A detailed comparative study of these four methods is then conducted. Finally, the existing problems and future studies that can be done in the field of person re-identification are analyzed and discussed.
Abstract: As an effective method for efficient precision machining of hard and brittle materials, ultrasonic-assisted machining has been widely researched and applied over the past years. As a result, higher requirements are put forward for the performance of ultrasonic-assisted machining equipment. The ultrasonic transducer is one of the core components of an ultrasonic-assisted machining system, which determines its machining performance. The study on the design method of an ultrasonic transducer is necessary for the establishment of an ultrasonic-assisted machining system. The four-terminal network method based on mechanic-electric analogies is an effective design method, which regards the mechanical vibration system as an electrical four-terminal network. The wave velocity of the mechanical wave in the vibration system can be equivalent to the current in the equivalent circuit, and the force impedance at both ends of the vibration system can be equivalent to the electrical impedance at both ends of the equivalent circuit. The size of the ultrasonic transducer can be calculated according to the electromechanical similarity theory and vibration boundary conditions. However, the conventional four-terminal network design method of the piezoelectric ultrasonic transducer (PUT) neglects the electromechanical coupling process inside the stacked piezoelectric ceramics (SPCs). The PUT designed by this method has a big size error and low output amplitude. Aimed to obtain a higher ultrasonic amplitude of PUT, the equivalent six-terminal network of SPCs considering electromechanical coupling is introduced into the traditional design method, and two PUTs of different sizes are designed by the four-terminal network and the six-terminal network, named transducer A and transducer B, respectively. The natural frequency and output amplitudes of the two PUTs are analyzed and compared by the finite element method, and the experiments further verified the validity of the theory and the simulation analysis. When the excitation voltage is the same, results show that the output amplitude of transducer B (designed by the six-terminal network) is 1.5 times higher than that of transducer A. Finally, applying a six-terminal network to the PUT designing can improve the vibration performance of the PUT effectively.
Abstract: Intelligent transportation systems (ITS) are the development direction of future transportation systems. ITS can effectively reduce traffic load and environmental pollution and ensure traffic safety, which has been a concern in all countries. In the field of intelligent transportation, vehicle detection has always been a hot spot but a difficult matter. To further improve the generalization, robustness, and real-time performance of the intelligent transportation system for the recognition of vehicles and different vehicle types, this study proposes an improved vehicle detection algorithm and chooses a road in the city as the background of the article. According to the characteristics of the detection region, the data set is constructed pertinently and the data set size is reduced using a video frame extraction method, aiming at achieving better detection performance with less training cost. The updating method of cosine decay with warm-up (CD) learning rate is then changed. An Adam gradient compression (GC) based on GC is proposed to improve the training speed, detection accuracy, and generalization ability of the YOLO v4 algorithm. To verify the effectiveness of the proposed algorithm, the trained network model is used to verify the quantitative vehicle type detection experiment of different density traffic flows after collecting the traffic flow information under actual road conditions. Experimental results show that the overall detection of the improved method is better than that of the original method. The accuracy rates of the network models trained by YOLO v4 and YOLO v4 GC CD under the blocking flow samples, synchronous flow samples, and free flow samples are 94.59% and 96.46%, 95.34% and 97.20%, 95.98%, and 97.88%, respectively. Simultaneously, the detection effect of YOLOV4 GC CD was verified at night and on rainy days with an accuracy rate of 92.06% and 95.51%, respectively.
Abstract: Porous media are widely found in underground rocks, biomimetic, and engineering materials. However, the current flow theory of fluids (liquid and gas, etc.) is incomplete to study flows in small and complex pores, thus a new theory is urgently needed for studying a large number of fluid flows in porous media. The theory of meso-scale flow in porous media is a “mysterious key” to unlock the flow of nano-micron porous media. At present, a large number of fluid flow problems need an immediate solution in porous media such as shale oil and gas development, soil seepage, human capillary network, and carbon nanotube (CNT). With the advancement of world petroleum engineering technology, unconventional oil and gas reservoirs have become the main areas of development in the petroleum industry. There are a large number of nano-scale pores in unconventional oil and gas reservoirs, and the existing macro-statistical methods of Darcy and non-Darcy percolation cannot reveal the nonlinear flow mechanism and effective production mechanism of fluid in mesopores. Thus, it is urgent to carry out theoretical research on meso-flow in porous media to provide a theoretical basis for unconventional oil and gas development. This paper summarizes the research results in this area, including those of the authors. The current research status of fine and meso flow in porous media is summarized from three aspects: (1) theoretical analysis, (2) experimental research, and (3) numerical model, focusing on key issues such as the relationship and characterization of meso-scale fluid flow interface and micro-mechanical properties, meso–macro network simulation, meso-scale fluid (oil/water, gas/water) flow, meso-dynamic mechanism, and mathematical models. On this basis, the importance of the research on the interface effect and meso-mechanical characteristics of fine and micro-scale fluid flow, the nonlinear flow mechanism of the fine and meso-scale fluids, the construction of a mathematical model reflecting the meso-scale flow under the action of micro-forces, and the formation of a network simulation method are introduced. The study provides certain guiding significance for unconventional oil and gas development processes, revealing the meso-causes affecting flow, clarifying the production mechanism under different conditions, and promoting further development of the discipline of seepage mechanics.
Abstract: This paper summarized the application, review, and award of research funding in the Mining and Metallurgical Engineering discipline at the Department of Engineering and Materials Science of the National Natural Science Foundation of China in 2021, as well as the final review and mid-term inspection of relevant projects. This paper also introduced the development strategy of the discipline and proposed the next steps for continuous improvement.
Monthly, started in 1955 Supervising institution：Ministry of Education Sponsoring Institution：University of Science and Technology Beijing Editorial office：Editorial Department of Chinese Journal of Engineering Publisher：Science Press Chairperson：Ren-shu Yang Editor-in-Chief：Ai-xiang Wu ISSN 2095-9389CN 2095-9389
