Abstract: This paper summarizes the application, review, and award of research funding in the Mining and Metallurgical Engineering discipline at the Department of Engineering and Materials Science of National Natural Science Foundation of China (NSFC) in 2022, basing on the following four research fields: petroleum engineering, mining engineering, safety science and engineering, and metallurgy and material processing engineering. A final review investigation and mid-term inspection of relevant projects are presented and next steps of the discipline are proposed as well.
Abstract: There are numerous issues in the mainstream process of alkali decomposition of tungsten ores, such as large water consumption, large amounts of wastewater, and high processing costs, which add the dual pressure of economic and environmental protection on smelting enterprises and prevent them from meeting the industry’s development needs. As a result of a series of studies on scheelite roasting and decomposition processes, our team innovatively proposed the use of acid roasting to develop the process of sulfate decomposition of scheelite so that CaWO4 in the scheelite could be transformed directly into WO3. In addition to WO3, the roasting products contained soluble Na2SO4 and insoluble CaSO4. Because CaSO4 can be dissolved in hydrochloric acid, it can be separated from WO3via hydrochloric acid leaching to further enrich WO3, resulting in a higher-grade material for subsequent procedures. In the presence of Na2SO4, its effect on the dissolution of WO3 or CaSO4 in hydrochloric acid will directly determine the separation effect of calcium and tungsten in the roasting products. Thus, using pure substances such as WO3, CaSO4, and Na2SO4 as raw materials, the dissolution behaviors of WO3, CaSO4, and WO3–CaSO4 in HCl–Na2SO4 solution were investigated separately via isothermal equilibrium dissolution to investigate the effects of hydrochloric acid concentration, sodium sulfate concentration, dissolution time, and dissolution temperature on the solubility of WO3, CaSO4, and WO3–CasO4 in HCl–Na2SO4 solution. The analysis shows that WO3 and CaSO4 have very different solubilities in hydrochloric acid. The solubility of CaSO4 in hydrochloric acid increases with temperature and hydrochloric acid concentration when the dissolution time is 0.5–2.5 h, the hydrochloric acid concentration is 1–5 mol·L?1, the molar ratio of HCl and Na2SO4 is 1∶2–2∶1, and the dissolution temperature is 40–80 ℃. The solubility of calcium sulfate in hydrochloric acid increases with the increase in temperature and hydrochloric acid concentration. When the temperature is 80 ℃ and the concentration of hydrochloric acid is 3 mol·L?1, the solubility of calcium sulfate in hydrochloric acid reaches a peak of 55 g·L?1. Due to the same ion effect, Na2SO4 can significantly reduce the solubility of CaSO4 and narrow the solubility difference between CaSO4 and WO3 in hydrochloric acid. CaSO4 has the highest solubility in HCl–Na2SO4 solution at 17.04 g·L?1. The dissolved WO3, whose solubility is maintained at 0.3–3 g·L?1, can be effectively recovered by using the current mature low-tungsten recovery process. Therefore, when CaSO4 and WO3 coexist in hydrochloric acid, increasing the concentration of hydrochloric acid and the dissolution temperature while decreasing the concentration of Na2SO4 can increase the solubility difference between them and achieve separation.
Abstract: With the deepening of the concept of interactive reaction and the development of several studies, metallurgists are no longer simply concerned with the metallurgical properties of a single charge. Instead, they comprehensively consider the interactive reaction of composite burdens. The interactive reaction is mainly affected by the chemical composition, microstructure, reduction temperature, and other factors of the ferrous burdens. In this study, taking a sinter with different basicities and a mixed ore of sinter and lump as the research object, the effect of sinter basicity on the smelting and dripping paraments of a composite burden and the interactive reaction between different burdens was investigated using melting–dripping equipment. The results show that the dripping temperature of a single sinter increases with sinter basicity. In the integrated burdens protocol, the proportion of lump ore increased, and the interaction between the burdens was enhanced, which is mainly manifested as a reduced softening start temperature and melting start temperature of the composite burden. The air permeability of the mixed charge was improved. A change of burden structure enhances the interaction between minerals with increasing sinter basicity, resulting in a change in the liquid phase composition, which reduces the melting point of the primary slag phase, and when the basicity of the sintered is too high, it will deteriorate the gas permeability of the material column. This result is not conducive to the intensive smelting of blast furnaces. At the same time, the sintered mineral phase changes throughout the reduction process were characterized using SEM-EDS and XRD, and the main phases in the slag phase are wustite and calcium silicate. The interactive reaction between the sinter and lump produces low melting point materials, which is verified by calculating the phase diagram of CaO–SiO2–FeO. With increasing sinter basicity, the content of 2CaO·SiO2 at different breakpoints decreased. This result shows that the high melting point phase formed during the reduction process of the sinter decreases, the liquid phase formation temperature of the composite burden decreases, and the interaction between the burdens increases. Therefore, appropriately increasing the sinter basicity and increasing the lump ore proportion benefits the enhanced smelting of a blast furnace. The theoretical and experimental results obtained in this research are of great importance for improving the production application of the proportion of lump in the furnace and developing efficient and low-carbon ironmaking.
Abstract: During the initial casting stage of the IF steel, the cleanliness of the first slab deteriorates. Steel plants treat the initial casting slabs as waste or demoting products. Moreover, the cleanliness deterioration of initial casting slabs leads to unstable quality and low product yield. In the present study, to investigate the cleanliness of continuous casting slabs and the optimization measures during the initial casting stage of the IF steel, the cleanliness of the initial casting slabs is evaluated by field sampling and experimental analysis. Moreover, the effect of the casting speed rising method on the cleanliness of the IF steel slab during the initial casting stage is investigated. Additionally, numerical simulations are conducted to reveal the level of fluctuations of the molten steel in the mold during the initial casting stage. The results show that the variations in T[O], [N], and the content of microinclusions in the slab decrease obviously along the casting direction. The contents of T[O] and [N] in the slab reach the normal slab level of 6 m (approximately 13×10?6) and 7 m (approximately 19×10?6) away from the dummy bar head, respectively. Nevertheless, the effects of the casting speed rising method on the contents of T[O], [N], and microinclusions in the initial casting slabs are inapparent during the open casting process. For the three conditions of open casting (different casting speed rising methods), the contents of the macroinclusions in the slab reach the normal slab level of around 2 m (approximately 2 mg/10 kg) away from the dummy bar head, respectively. Subsequently, the fluctuation of the macroinclusion content can be determined. Furthermore, under the condition of “quick-slow” casting speed rising, the fluctuation can be quickly alleviated, and the macroinclusion content normalizes. Numerical simulations reveal that the variations in the fluctuation level of the molten steel at different positions (near the nozzle, a quarter of the width, and near the narrow face) in the mold during the initial casting stage of the three casting speed rising modes are similar. First, the fluctuation level is extremely intense. Then, the fluctuation level gradually weakens for some time. Finally, the fluctuation level of the molten steel at different positions in the mold stabilizes. Additionally, the numerical simulation results reveal that the slab cleanliness can quickly normalize (430 s after initial casting and about 5 m away from the dummy bar head) under the “quick-slow” casting speed rising mode during the initial casting stage.
Abstract: The composite oxides of Ti and Zr can effectively induce acicular ferrite nucleation and refine austenite grain size. To study the transformation mechanism of acicular ferrite in Ti–Zr treated steel, the mass fraction of 0.038% titanium and 0.008% zirconium were added to low alloy steel by melting in a 25 kg vacuum induction furnace. The effect of austenitizing temperature on acicular ferrite transformation behavior was observed in-situ using a high-temperature laser confocal microscope: the samples were heated to 1250, 1300, 1350, and 1400 ℃ at a heating rate of 5 ℃·s?1 and then cooled to 400 ℃ at a cooling rate of 3 ℃·s?1 after holding for 300 s. The ferrite transformation behavior of samples during the above process was observed using a high-temperature confocal microscope. The inclusion composition of Ti–Zr treated steel and the nucleation of acicular ferrite on the inclusion surface were observed using a scanning electron microscope. The variation in microstructure at different austenitizing temperatures was observed using an optical microscope. The austenite grain size was found to increase from 125.6 to 279.8 μm with increasing austenitizing temperature from 1250 to 1400 ℃. The initial transformation temperature of acicular ferrite and side-plate ferrite increased, reached a maximum at 1350 ℃, and then decreased. The volume fraction of acicular ferrite increased from 39.6% to 83.6%. In Ti–Zr treated steel, the size of complex inclusion with Zr–Ti–O in core and Al–Ti–Zr–O in exterior and MnS precipitated on the surface was mainly concentrated in 1–3 μm. It could effectively promote acicular ferrite nucleation. The Mn-poor region and the good lattice relationship between complex inclusions and ferrite were the mechanisms by which the type of inclusions in the steel could promote acicular ferrite nucleation. Using classical nucleation theory, the nucleation potential of acicular ferrite under different conditions was calculated. The results showed that when the austenitizing temperature was 1300 ℃, the nucleation potential of acicular ferrite was the strongest, reaching 191.7 mm?2. The calculation results were consistent with the variated law of acicular ferrite volume fraction. An increase in austenite grain size led to a decrease in polygonal ferrite nucleation sites, an increase in acicular ferrite nucleation space, and the formation of many inclusions that effectively induced nucleation of acicular ferrite treated by titanium and zirconium, which increased the acicular ferrite volume fraction.
Abstract: Austenite reversion has been widely used in the traditional heat treatment of steels, and recently, it has been used in the fabrication of advanced high-strength steels. The microstructure of reverted austenite significantly influences the final microstructure and properties of steel; thus, it is crucial to understand the formation of globular austenite to accurately grasp its reversion behavior. In this paper, an Fe–2.5Mn–1.5Si–0.35C alloy was chosen as the research object, and the evolution of intragranular globular austenite and finally transformed austenite grain size were studied under different pre-tempering conditions using a metallographic optical microscope, scanning electron microscope, and electron backscatter diffraction. It was found that as the pre-tempering temperature was increased from 350 ℃ to 650 ℃, the volume fraction of intragranular globular austenite first increased and then rapidly decreased. At the pre-tempering temperature of 400 ℃, the volume fraction of intragranular globular austenite initially increased and remained stable thereafter, when the pre-tempering duration was increased from 1 to 10 h. Fine cementite particles were primarily formed immediately before the reversion in the non-tempered or low-temperature pre-tempered initial structures. This provided less effective nucleation sites for the formation of intragranular globular austenite. Therefore, lesser intragranular globular austenite grains were formed, thereby resulting in relatively coarse finally transformed austenite grains after reversion. The cementite particles were gradually coarsened as the pre-tempering temperature was increased to 550 ℃, thereby increasing the number of effective nucleation sites for the formation of intragranular globular austenite. Conversely, when the martensite samples were pre-tempered at a high temperature of 650 ℃, Mn is seriously enriched into the cementite particles before the reversion, largely reducing the driving force for reversion. This resulted in the growth of intragranular globular austenite under the partitioning local equilibrium mode, with a slow growth rate, resulting in a low volume fraction. Therefore pre-tempering can effectively promote the formation of intragranular globular austenite. Owing to its multiple orientations, increased intragranular globular austenite formation resulted in significantly refined austenite grains after reversion. This study provided a new strategy to regulate the formation of intragranular globular austenite and finally transformed austenite grain size by controlling the size and composition of cementite particles through pre-tempering without changing the chemical composition of the steel.
Abstract: Corrosion is a global problem affecting a wide variety of the mechanical structures of piping, buildings, transportation, sewage, and automotive parts. Corrosion is an abiotic electrochemical reaction of metal oxidation with oxygen and water. Under anoxic conditions, the only reactant available for iron oxidation is water-derived protons. The kinetics of this reaction is extremely slow. However, this behavior contrasts with extreme corrosion observed in anoxic environments, demonstrating that biological processes play an important role in iron and steel corrosion. Therefore, among the different corrosion mechanisms, microbiologically influenced corrosion (MIC) is the most common and the most closely related to the complex processes connected with microorganism activity. Biocorrosion is a well-established, highly destructive phenomenon, and MIC can accelerate the deterioration of metal, plastics, stone, concrete, and wood, leading to human and environmental risks as well as substantial economic losses, which make MIC an important research topic. It is estimated that 20% or more of corrosion losses can be attributed to MIC. The main types of bacteria associated with corrosion are SRB, SRA, NRB, APB, IOB, IRB, SOB, and bacteria-producing organic acids, exopolymers, or slime. MIC is always associated with biofilm. Although classical corrosion theories can explain some MIC phenomena, the limitations of these mechanisms are exposed when MIC becomes a serious concern in real industrial applications. With increasingly more research on corrosive bacteria, people have a more comprehensive and in-depth understanding of the mechanism of MIC. In this work, the species and characteristics of microorganisms easily leading to corrosion are analyzed, such as sulfate-reducing bacteria, nitrate-reducing bacteria, and iron-oxidizing bacteria. Different mechanisms of MIC are discussed using the concepts of bioenergetics, electron transfer theories, and respiration types. The latest research progress on the microbial corrosion mechanism, including extracellular electron transport, metabolite corrosion, and the concentration differential battery, was reviewed. The process of microbial corrosion often involves more than one mechanism. Different microorganisms grow in different environments, and their metabolic processes differ. Therefore, obtaining a unified corrosion mechanism is difficult, so we can only judge which mechanism plays the main role according to the specific situation. This review provides theoretical guidance for the diagnosis, prediction, and prevention of microbial corrosion under anaerobic and aerobic conditions in the industry.
Abstract: China is rich in marine resources, and with the development of its economy and the improvement of its transportation level, the use of immersed tunnel technology is increasingly more extensive. The Shenzhen–Zhongshan Bridge is the first steel shell immersed tunnel in China. The immersed tunnel is located in a sea mud area that is not easy to inspect and maintain, and its steel shell structure is eroded by seawater, which shortens its service cycle, and severe corrosion affects its safe operation. Its durability requirement is 100 years. For the service environment and ultrahigh durability requirements of the Shenzhen–Zhongshan Bridge steel shell concrete immersed pipe and many other characteristics, at present, few engineering and research references at home and abroad can be used. Thus, the corrosion development law of the outer wall of an immersed steel shell in a marine environment must be studied and revealed. In this work, dissolved oxygen (15.2 mg·L–1) was artificially added to a simulated seawater solution as a depolarizing agent to realize the acceleration process of a corrosion simulation acceleration test in the laboratory. The test set cycle was 1, 7, 15, 30, 90, 180, and 365 d, and the test temperature was 25 ℃. Through the electrochemical impedance spectroscopy (EIS), the Tafel polarization curve, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), confocal laser scanning microscopy (CLSM), and other analytical and testing methods of samples with different test cycles, the corrosion occurrence and development law of Q390C low-alloy high-strength structural steel used in deep–medium channel immersed tunnel steel shells under simulated seawater conditions was studied. The corrosion products of Q390C steel in seawater are mainly found to be Fe3O4, α-FeOOH, γ-FeOOH, and a small amount of CaCO3, and their uniform corrosion and local corrosion rates decrease exponentially and eventually tend to stabilize. CLSM test shows that the surface of the specimen begins to corrode uniformly after a test cycle of 15 d, and the pitting corrosion pit depth of the specimen with a test cycle of 365 d can reach 99 μm. The long-term accelerated corrosion test of the steel shell of an immersed tunnel in seawater in this paper is of great importance to ensure the long-life durability of immersed tunnels in marine engineering and similar construction projects.
Abstract: Oil spill pollution seriously endangers human and ecosystem health. Therefore, it is urgent to develop oil-absorbing materials to effectively remove oil spill pollution. Among the traditional oil-absorbing materials, natural organic adsorption material has low oil absorption capacity and hydrophilicity; inorganic adsorption materials are difficult to recover and have low oil absorption efficiency and high price; and although the synthetic organic adsorbent has outstanding oil absorption capacity, its biodegradation is poor. Silica aerogel (SA) has the characteristics of high porosity, low density, and high specific surface area, which make it an excellent oil-absorbing material. However, the hydrophilic surface and pearl necklace structure of SA limit its wide applications in the oil absorption field. Hydrophobically modified hydrophobic silica aerogel (HSA) has not only excellent SA characteristics but also good hydrophobic/lipophilic properties. In this paper, focusing on HSA preparation by surface posttreatment modification and coprecursor modification, the research progress on these two methods combined with supercritical drying and ambient pressure drying is systematically introduced, and the advantages and disadvantages of the two methods are analyzed and summarized. The coprecursor modification is mainly combined with a supercritical drying process to prepare HSA, while the surface posttreatment modification is often combined with an ambient pressure drying process. Both methods normally use silylating agents as hydrophobic modifiers. The surface posttreatment modification does not change the formed pore structure, and the pore size and particle size of HSA are relatively uniform. However, the modification process of surface posttreatment is long, the solvent consumption is large, and the cost is high. In addition, incomplete internal modification may be a problem. In the coprecursor modification method, wet gel is formed and modified simultaneously, shortening the modification time and saving costs. The prepared HSA of coprecursor modification has a larger specific surface area and better hydrophobicity, but its pore size is uneven, and the introduced hydrophobic groups are limited. Excessive silylating agents affect the sol–gel process of HSA. In addition, the current methods for strengthening HSA mechanical properties and the research progress on HSA oil absorption properties are reviewed. Finally, based on the current development of HSA as oil-absorbing materials, the development direction of these materials is discussed, for example, developing low-cost and eco-friendly raw materials, shortening the hydrophobic modification process, preparing bulk HSA, strengthening the mechanical properties, and improving the oil-absorbing properties of HSA.
Abstract: Photocatalytic antibacterial materials have been popularized and widely used in the disinfection of municipal water, the large-scale wastewater sterilization treatment of industry, and medical treatment. Their antibacterial theory has also been continuously studied and improved, and the reactive oxygen species (ROS) antibacterial mechanism has the highest acceptance by the public. The role of ROS is the main bactericidal mechanism of photocatalytic antibacterial agents, and it is also the mechanism explanation at the molecular level in the fields of organic pollutant degradation and biological pathology. ROS at an abnormal steady-state concentration attacks the organic structure outside the cell and enters the cell, causing oxidative stress reactions inside the cell and irreversible damage to the cell until apoptosis. Therefore, a systematic analysis of the production pathways, principle of action, and corresponding detection methods of active oxygen is of great importance for improving the antibacterial activity of photocatalytic antibacterial agents and exploring the antibacterial mechanism of active oxygen. First, this article introduces the production mechanism of active oxygen in photocatalytic materials and its antibacterial performance. Particularly, the modification method of constructing heterojunctions and introducing oxygen vacancies is the main way to increase active oxygen production. Second, this article summarizes the production process and mechanisms of the main ROS, such as the superoxide anion radical (·O${}_2^- $), hydrogen peroxide (H2O2), singlet oxygen (1O2), and the hydroxyl radical (·OH), as well as the antibacterial process. Detection methods are summarized for four ROS, including direct methods and indirect methods as well the specific and selective reaction principle of probe molecules with ROS. Furthermore, the influencing factors of the total concentration of ROS excited by photocatalytic materials are sorted out, and a modification direction for producing ROS is proposed. This paper proposes the problems existing in the research on the action mechanism of ROS and the deficiencies in the detection methods of ROS and their specific interaction with cells. It is suggested to carefully analyze the antibacterial mechanism of ROS at the biological component level under the guidance of the generation chain of ROS and the dynamic balance system of various ROS. Finally, suggestions are made on the design and application of active oxygen antibacterial materials, and the development prospects are addressed.
Abstract: Steel slag–peanut shell-based activated carbon was prepared using ultrafine steel slag powder and peanut shells through microwave processing. The response surface method was used to evaluate the effects of microwave power, impregnation ratio, steel slag content, and steel slag particle size on the rate of the adsorption of formaldehyde gas by the prepared activated carbon. Subsequently, optimum parameters were calculated for the preparation of activated carbon with the maximum rate of adsorption for formaldehyde gas adsorption. Finally, the activated carbon was characterized by an X-ray infrared spectrometer, field emission scanning electron microscope, and specific surface area and pore size analyzer. Results revealed that the activated carbon prepared using 530 W of microwave power, steel slag powder corresponding to a mesh size 1160, steel slag content equal to 10.8%, and impregnation ratio of 1.25 has the highest formaldehyde adsorption rate. According to the established regression model, the theoretical adsorption rate of formaldehyde gas will be 94.96% under the above optimal preparation conditions. Thus, the prepared activated carbon had a formaldehyde adsorption rate of 94.14%, which is within a 5% error range of the adsorption rate estimated by our regression model for the same conditions. We further demonstrated that our response curve model can predict the adsorption rate of the activated carbon prepared by this process efficiently and that it is feasible to optimize the preparation of activated carbon by the response surface method. Furthermore, the regression analysis further reveals that the degree of influence of the four factors related to this method of preparing activated carbon on the rate of formaldehyde gas adsorption is in the following order, from large to small: microwave power, steel slag content, impregnation ratio, and steel slag fineness. The mutual interaction of the four influencing factors on the formaldehyde gas adsorption rate can be intuitively observed through the three-dimensional response surface graph. Pore structure analysis of the activated carbon prepared using the optimal preparation conditions revealed that it has an H3-type hysteresis loop and a flat-panel slot-like structure. The pore size distribution is uneven, with predominant micropores and small-sized mesopores. Fourier-transform infrared spectroscopy analysis showed that after adding steel slag for modification, the activated carbon had more acidic functional groups, which is beneficial to the adsorption of formaldehyde. Morphological analysis reveals that the layered structure of the activated carbon is clear and that adding a small amount of steel slag is beneficial to improve the rate of pulverization.
Abstract: With the development of the industry of semiconductor integrated circuits, microelectromechanical system (MEMS) products have made rapid progress. The development of MEMS and the combination of sensor technology have yielded compact sensors with increased functions and intelligence levels. MEMS-based microhotplate (MHP)-type metal oxide methane sensors have the advantages of low power consumption and fast response and have been widely used in methane detection applications. In particular, ZnO methane-sensitive materials have attracted significant attention due to their high sensitivity, small poisoning effect, and low operating temperature. Notably, the response performance of sensors prepared from these sensitive materials is still significantly affected by the heating temperature and thermal distribution of the MEMS-based MHP. The purpose of our experiment is to optimize the heat generation of the heating electrodes of MHP, optimize the thermal distribution of MHP, and further reduce the power consumption of MHP sensors. The heating electrodes of MHP are made of platinum materials that have high thermal conductivity and stable performance. In this study, we use the Multiphysics module in the finite element analysis software COMSOL to simulate and analyze the temperature in the physical field for the two structures of serpentine platinum heating electrodes of MHP. By comparison, the structure of the heating electrodes affects the temperature distribution under the same working conditions. The structure with a larger width in the middle of the heating plate electrode and gradually narrowing to both sides generates more heat than that with the same width. When the heating plate reaches 300 ℃, it needs about 75 mW of power. Next, ZnO thin film methane sensors were constructed by sputtering ZnO methane-sensitive materials on the interdigital electrode of a commercial MHP, and the response of the gas sensor was tested using the HIS9010 of Hefei Micro-Nano Company. The static measurement method was used to inject methane gas into a 1-L gas chamber. In order to verify the superior response of our sensor, it has been compared that performance of commercial methane sensors and ZnO methane sensors made by. The response linearity in the interval is relatively good, and the response value for 10000×10?6 methane reaches 30. The response of our fabricated sensor is higher than those of existing domestic and foreign commercial methane sensors, showing significant potential in related applications.
Abstract: Lithium-ion batteries are widely used in electric vehicles and energy storage systems. As a prerequisite for the safe and efficient application of lithium-ion batteries, battery management systems have received extensive attention worldwide. Among these prerequisites, the state of charge (SOC), as the basic parameter of battery management system online application, is crucial for the safe and efficient operation of battery management systems. However, measurement noise decreases the accuracy and robustness of the state of charge estimation. To reduce the impact of noise on the state of charge estimation of lithium-ion batteries, a novel SOC estimation method based on an extreme learning machine and a maximum correlation entropy square root volumetric Kalman filter is proposed in this paper. First, the extreme learning machine is used as the measurement equations of the Kalman filter because of its good generalization and fast running speed, and the voltage and current are selected as the model input; second, on the basis of the gray wolf optimization algorithm, the extreme learning machine hyperparameters are thoroughly optimized to improve the accuracy of the state of charge estimation for lithium-ion batteries; finally, on the basis of the framework of the maximum correlation entropy square root volumetric Kalman filter, a closed-loop estimation is realized to further reduce the state of charge estimation error caused by the measurement noise of voltage and current. The proposed method can simplify the time-consuming parameter adjustment of an extreme learning machine and show superior robustness under low-quality measurement. The proposed method is validated under multiple drive cycles and a wide temperature range to verify its generalization performance. The test results show that the proposed method substantially improves the accuracy of lithium-ion battery state of charge estimation. At the same time, the average running time of the proposed method is only one-third of that of long short memory neural networks and gate recurrent unit neural networks. Under complex driving conditions and a large temperature range, the root mean square error of the proposed method is less than 1%, and the maximum error is less than 3%. Furthermore, two case experiments are performed to evaluate the robustness of the proposed closed-loop estimation approach, and the results obtained when data have an initial state of charge error and measurement noise verify the superior robustness of the proposed approach compared with long short memory neural networks and gate recurrent unit neural networks.
Abstract: Accurate segmentation of brain tumors from magnetic resonance images is the key to the clinical diagnosis and rational treatment of brain tumor diseases. Recently, convolutional neural networks have been widely used in biomedical image processing. 3D U-Net is sought after because of its excellent segmentation effect; however, the feature map supplemented by the skip connection is the output feature map after the encoder feature extraction, and the loss of original detail information in this process is ignored. In the 3D U-Net design, after each layer of convolution, regularization, and activation function processing, the detailed information contained in the feature map will deviate from the original detailed information. For skip connections, the essence of this design is to supplement the detailed information of the original features to the decoder; that is, in the decoder stage, the more original the skip connection-supplemented feature maps are, the more easily the decoder can achieve a better segmentation effect. To address this problem, this paper proposes the concept of a front-skip connection. That is, the starting point of the skip connection is adjusted to the front to improve the network performance. On the basis of this idea, we design a front-skip connection inverted residual U-shaped network (FS Inv-Res U-Net). First, the front-skip connections are applied to three typical networks, DMF Net, HDC Net, and 3D U-Net, to verify their effectiveness and generalization. Applying our proposed front-skip connection concept on these three networks improves the network performance, indicating that the idea of a front-skip connection is simple but powerful and has out-of-the-box characteristics. Second, 3D U-Net is enhanced using the front-skip connection concept and the inverted residual structure of MobileNet, and then FS Inv-Res U-Net is proposed based on these two ideas. Additionally, ablation experiments are conducted on FS Inv-Res U-Net. After adding the front-skip connection and the inverted residual module to the backbone network 3D U-Net, the segmentation performance of the proposed network is greatly improved, indicating that the front-skip connection and the inverted residual module help our brain tumor segmentation network. Finally, the proposed network is validated on the validation dataset of the public datasets BraTS 2018 and BraTS 2019. The Dice scores of the validation results on the enhanced tumor, whole tumor, and tumor core were 80.23%, 90.30%, and 85.45% and 78.38%, 89.78%, and 83.01%, respectively; the hausdorff95 distances were 2.35, 4.77, and 5.50 mm and 4, 5.57, and 6.37 mm, respectively. The above results show that the FS Inv-Res U-Net proposed in this paper achieves the same evaluation indicators as advanced networks and provides accurate brain tumor segmentations.
Abstract: Because structural parameter matching has a strong influence on the service behavior of planetary roller screw mechanisms (PRSM), understanding how to effectively design the structural parameters of PRSM is highly important in practical industrial applications. This study proposes a parameter optimization model based on a crow search algorithm (CSA) to solve the structural parameter matching problem of PRSM. The relationship between the main structural parameters of PRSM can be deduced according to the working principle and geometric conditions. The screw, roller, and nut space spiral surface equation are established by considering the influence of the meshing point position of PRSM on thread meshing clearance. The relationship between the meshing point position and PRSM tooth thickness is obtained using the tangent contact condition of the spiral surface. To achieve no backlash meshing and improve PRSM transmission accuracy, the thread tooth thickness of the screw, roller, and nut can be adjusted. According to the meshing relationship between the thread pair and the gear pair of PRSM, the structural parameters of the annular gear and the gear at the end of the roller are determined. The normal vectors at the meshing point of the screw, roller, and nut are calculated using space spiral surface equations. To test the strength of the PRSM, static analysis of the roller is used to deduce the force relations between the main parts of the PRSM. PRSM structural parameters serve as design variables. An optimization goal is to reduce the outer diameter of the nut, the nominal diameter of the screw, and the length of the roller. The spatial structure constraints and component strength constraints of PRSM are considered. The CSA was introduced to be the optimization algorithm. The parameter optimization model of PRSM is established for achieving optimum matching of the optimization variables. Finally, using the proposed optimization model, three groups of PRSM structural parameters are obtained for three different types of load. In this study, the optimization results are compared with a foreign PRSM product manual to validate the effectiveness of the optimization model. The results show that the PRSM structural parameters obtained from the proposed model are essentially consistent with those from the foreign PRSM product manual. Furthermore, the proposed model provides the structural parameters of thread teeth, which are not included in the foreign product manual. The proposed PRSM optimization model is promising for its application in actual production.
Abstract: During tunnel excavation, the stress of the surrounding rock is redistributed, leading to a local stress concentration around the tunnel. In addition, blasting excavation and other factors lead to a strength reduction of rock mass around the tunnel and eventually form a relaxation fracture zone (loosening zone). If supporting measures are not adopted in time during tunnel excavation, the rock strength in the loosening zone will be further reduced and eventually lead to overall instability and collapse. To simulate the bolt/cable supporting effect on the loosening zone and surrounding intact rock, a block–particle–bar coupling algorithm based on penalty springs is proposed. This coupling algorithm is based on the continuum–discontinuum element method (CDEM). CDEM is a dynamic, explicit solution algorithm based on a generalized Lagrange system. A strict controlling equation is established by the Lagrange energy system, and an explicit iterative solution of the dynamic relaxation method is used to realize a unified description of continuous and discontinuous media. The progressive failure of a solid is analyzed through the fracture of the bond between the blocks or particles. Using CDEM, the entire process of the solid from continuous deformation to fracture and movement can be simulated. In the block–particle–bar coupled algorithm, discrete particle clusters are adopted to represent the broken rock mass inside the loosening zone around the tunnel, block elements are used to represent the intact rock mass outside the loosening region, and bar elements are introduced to describe the supporting structures, such as bolts and cables. A contact coupling mode is adopted between particles and blocks, one normal spring and two tangential springs are constructed, and brittle Mohr–Coulomb fracture constitutive law and tensile fracture constitutive law are introduced to represent contact behavior. To realize the transmission of force and displacement, the interpolation coupling approach is adopted between the elements of bars and the elements of discrete particles or blocks. In this coupling mode, penalty springs Sgn and Sgs along and perpendicular to the axis of the bar, respectively, are established. Sgn and Sgs are mainly used to describe the pulling and pushing effect and the lateral compression effect between the bar and the surrounding rock, respectively. The coupling algorithm described in this paper is adopted to simulate the elastic field of a circular shield tunnel, rectangular tunnel reinforced by prestressed rock bolts, reinforcement of full-anchored rock bolts on surrounding rock, and the tunnel support effect in a jointed rock mass. The results of the four numerical cases show the accuracy and rationality of the coupling algorithm. Using this proposed algorithm, the progressive failure process of rock tunnels under high ground stress and the supporting process by lining and bolt (cable) can be accurately simulated.
Abstract: Low-carbon development of the iron and steel industry is critical to China’s goal of carbon neutrality and emission peaking. The carbon emissions of China’s iron and steel industry are calculated using the emission factor method in this paper, and the influencing factors of emission growth are investigated using the two-stage logarithmic mean divisia index (LMDI). The results show that carbon emissions from the steel industry continue to rise, reaching a stage peak of 1.848 billion tons in 2014 before declining. Carbon emissions fall by 52.4% during this period, energy intensity decreases by 52.9% per ton of steel; the decline in energy intensity will be much smaller in the future. The scale effect is the most important factor in the growth of carbon emission, accounting for 178.17% of the total, whereas energy intensity is the most important restraining factor, accounting for 76.02% of the total. However, the impact of energy structure and emission factors remains unclear. This is due to the small change in the energy mix and emission factors. The scale effect, which is a major contributor to rising carbon emissions, is broken down once more. Capital stock and total factor productivity drive carbon emission growth, whereas labor factors reflect the transition of the industrial population to low-carbon industries. The STIRPAT model predicts future carbon emissions from the iron and steel industry. The results of the scenario analysis show that carbon emissions will peak in 2025 under the baseline scenario, with carbon emissions totaling 1.904 billion tons. The peak time for carbon emissions in the low carbon scenario is 2021, and the peak is lower, with carbon emissions of 1.867 billion tons. Carbon emissions have already peaked in 2020 in the strong low-carbon scenario and will further decline to 1.439 billion tons in 2030, which is equivalent to 2010 carbon emissions. However, the rapid development scenario will not be able to reach a peak in carbon dioxide emissions before 2030. The forecast results show that both social and economic factors, as well as steel production factors, can have a significant impact on the overall industry’s carbon emission, implying that both the supply and demand sides must contribute to emission reductions. Controlling new capacity, transforming process structure, reducing fossil energy consumption, and promoting the use of hydrogen energy in the smelting process will be critical in the future for the industry’s low-carbon development.
Abstract: Research in the field of oil and gas development has focused on the production of unconventional reservoirs all over the world. Unconventional oil and gas reservoirs have poor flow conditions, and the interaction of flow, stress, and temperature fields is very complex. Therefore, multiphysical field coupling is essential. The previous application of multiphysical field coupling theory has defects such as oversimplification and inadequate adaptability. Furthermore, the lack of adaptive production practices and effective development plans limits large-scale and efficient development, and there is an urgent necessity to investigate the adaptive multiphysical field coupling theory. Currently, the core rheology in fluid–solid coupling settings can often be measured by a triaxial test system under high temperature and pressure conditions combined with flow experiments. Moreover, the changes in pores and fractures can be tested by micro-CT and SEM. In addition, adsorption is considered an exothermic process, and desorption is deemed a heat-absorbing process, so the reservoir temperature decreases at the location where desorption occurs. Therefore, the production of unconventional oil and gas triggers a series of interactions. As the fluid flows into the wellbore through the fractures, the pressure drop increases the effective stress, decreasing the average pore radius and altering the inherent permeability. Moreover, the change of pressure causes a variation in the micro-flow effect, significantly impacting the apparent permeability, and the heat variation during desorption and adsorption also changes the flow condition as well as the physical properties of the fluid. As a result, these physical fields are closely related. A series of fully coupled partial differential equations are necessary to define the production process by modeling the dynamic porosity and permeability in various flow sectors to distinguish the interactions between different zones and physical fields. These complex interactions generally need to be solved by numerical methods. Thus, a simulator is needed that satisfies the accuracy requirements to match the actual situation. Moreover, adaptability to the decoupling process and acceptable speed requires research for high-performance computing solutions that can perform distributed or cloud computing for a large-scale unconventional reservoir simulation. Future research is necessary for laboratory measurements under realistic stress and temperature environmental conditions of the formation and hydrocarbon adsorption experiments. There should be further understanding of scientific issues such as the plastic strain of the porous rocks, changing stress environment after refracturing, and mixed hydrocarbon transport models with varying stress and temperature. This article further clarifies the dynamics and determines effective production methods of unconventional reservoirs in China to promote the development of flow mechanics.
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
