Abstract: In recent years, paste technology has been rapidly promoted in domestic mines. It is a key technology for realizing green mining because it can effectively solve environmental and safety problems caused by mining. With the progress in science and technology, the research level of paste technology is constantly improving. Thickening technology of tailings is the primary procedure of paste backfill technology in metal mines, which can significantly improve the efficiency of tailings dewatering and utilization rate of tailings. Tailings thickening technology is an important part of the green development of mines. This paper presented a summary of the development process of tailings thickening and dewatering technology, dividing the development stage of the thickener into three: (1) ordinary thickener stage, (2) high-efficiency thickener stage, and (3) paste thickener stage. The application status of the thickening process of tailings and several typical application cases at home and abroad were also described. In addition, this paper explored different theories, including the single flocculation theory, multiple flocculation theory, bed compression theory under static/dynamic compression, and gravity thickening theory, along with the corresponding latest research progress of each theory. This paper also presented the main research methods of thickening of tailings, namely the static settlement experiment, small-scale thickening experiment, and semi-industrial thickening experiment. Advanced observational methods such as focused beam reflection measurement technology (FBRM) and particle video microscope technology (PVM) were also introduced. Moreover, the paper expounded on the research status of numerical simulation of tailings thickening technology and highlighted that the tailings thickening and dewatering technology is still in the development stage with some underlying problems, such as the instability of the key parameters of tailings thickening, the untimely production control of tailings thickening, and the imperfect information platform of tailings thickening. Overall, the development of tailings thickening technology is still facing numerous challenges. Finally, the direction of the development of tailing thickening technology is proposed in terms of personalization, automation, and intelligence.
Abstract: The development and utilization of coal resources have caused serious surface collapse and destruction and ecological, environmental pollution. As the main method of green mining, backfill mining fills gangue and other wastes into the goaf to control the surface subsidence and processing coal gangue, which has broad application prospects. Aiming at the practical needs and significance of reducing gangue emission and controlling surface subsidence caused by high-intensity mining in fragile environmental areas in western China, this work proposed a short-wall continuous mining and continuous backfilling (CMCB) cemented-fill mining technology. On the basis of studying the mining principle of the short-wall CMCB cemented-fill mining technology, this work introduced layouts of this technology’s working face and mining and filling crafts according to the longwall working face and the short-wall working face, respectively, realizing the parallel operation of mining and backfilling by skip mining. The mineral composition, microscopic characteristics, and gradation characteristics of various filling materials were analyzed, and the strength and flow characteristics of the cemented filling materials under different proportions were tested on the basis of a filling material test combined with pipeline transportation characteristics and filling methods of the coal mine cemented-fill slurry. The composition and overall design ideas of the filling system of this technology were put forward, including four parts: slurry preparation system, pipeline transportation system, monitoring system, and working face filling system. The on-site test showed that the short-wall CMCB cemented-filling mining technology achieves a compression ratio of more than 98% in a 5-m thick near-level coal seam. The maximum roof subsidence is 102 mm, and the maximum surface subsidence is 8.9 mm. 245000 t of gangue were used, and a good application effect was observed.
Abstract: Some beneficiation circulating water contains excess highly dispersed suspended particles, which are difficult to clarify only by simple concentration and sedimentation and cannot meet the requirements of reuse. To solve this problem, a clarification device was developed for removing the solid suspended matter from beneficiation circulating water, which consists of a hydraulic circulation area and a particle sedimentation area and integrating mixing, flocculation, and sedimentation. The flow field inside the gadget has a big influence on how well it works. The structural and operating parameters of the gadget were improved using the computational fluid dynamics approach to increase the device’s performance. A two-dimensional physical model of the deep clarification device for beneficiation circulating water was established. Numerical simulation research on its main structural parameters and operating parameters were conducted by using software Fluent and choosing the Mixture multiphase flow model and RNG k?ε turbulence model. The effects of feed water nozzle length, throat to nozzle diameter ratio, sludge settling area opening size, and device diameter on the internal flow field were investigated. The average turbulent kinetic energy in the sludge settling zone can be reduced by reducing the length of the nozzle in the hydraulic circulation region, increasing the ratio of the throat to nozzle diameter and the opening size of the sludge settling area, and increasing the diameter of the device. Due to the fact that the turbulent kinetic energy is the kinetic energy of fluid produced by turbulent pulsation, the turbulent degree of the flow field in the sludge settling area is reduced, the effect of turbulent flow in the flow field on particle settling is weakened, and the removal effect of the device on suspended particles is improved. Simultaneously, it is found that at the same suspended solids concentration, reducing the inlet flow rate or increasing the suspended particle size helps to improve the removal rate of suspended solids. When the inlet flow rate is 0.1 m·s-1 and the coagulated suspended particles form particles with particle size more than 100 μm, the removal effect of slime particles in beneficiation circulating water is remarkable.
Abstract: The friction welding (FW) technology is a kind of solid-phase hot pressing welding method applied to the connection of similar or dissimilar materials. During the FW process, welding heat is generated by the pressure and high-speed relative motion between the joint interfaces of the workpieces. After the joint interfaces and their neighborhood arrive at the thermoplastic state, the workpieces are pressed into a whole by upsetting. FW has a wide range of weldability (e.g., carbon steel, alloy steel, non-ferrous metals, other materials of the same kind, dissimilar metal materials, and metal and non-metal materials with completely different properties) and can obtain welded joints with excellent properties (closed to base metal) and fewer defects (e.g., cracks, pores, and segregation); thus, it has high reliability to welded joints. As its advantages, FW exhibits low energy consumption (i.e., 10%–20% of fusion welding), high efficiency (i.e., only a few seconds to realize an effective joining of the workpieces), and environmental friendliness (i.e., no welding rod, wire, flux, or protective gas and no arc, spatter, smoke, or slag as in fusion welding) and can easily realize automation and large-scale production. FW is widely used in high-tech manufacturing in various industries, including in the automobile, aviation, aerospace, nuclear energy, oil drilling, marine development, and electric power industries. On the basis of the classification and the brief description of FW, the present situation of the research, development, and application of the continuous-drive FW (CDFW) technology was comprehensively sorted out and analyzed in-depth in this paper. This study involved the CDFW process characteristics and main process parameters, process exploration, influence of the process parameters on welded joint properties, numerical analysis, simulations, process parameter optimization, CDFW process innovation for dissimilar metals and non-metallic materials, practical engineering applications, and welding equipment, among others. The aspects of the potential applications of the FW technology, core scientific issues, research and development of the novel FW equipment, numerical analysis and simulation, and combination with emerging technologies associated with the CDFW technology were also reviewed and discussed.
Abstract: Solid oxide fuel cells (SOFCs), which are electrochemical devices that generate power with high efficiency, free of pollution, and nonregional restrictions, have attracted extensive attention. A traditional SOFC works at temperatures more than 800 °C, which introduces several severe problems or drawbacks, such as the high possibility of interfacial reaction between the cell components, easy densification of the electrode layer, possible crack formation owing to mismatch in the thermal expansion of cell components, and the requirement for a high-cost LaCrO3 ceramic as the interconnect material. Thus, reducing the operating temperature of SOFCs has become a consensus among researchers for the benefit of long-time operation. On the other hand, the operation of SOFCs at lower temperatures introduces several major issues, such as the increase in electrode resistivities and polarization losses of electrode reactions, particularly the oxygen reduction reaction in the cathode. Presently, perovskite-based oxides with mixed ion-electron conductivity (MIEC) are the most promising cathode materials for intermediate temperature SOFCs. Among the various mixed conducting oxides, cobalt-containing ones usually show excellent ionic conductivity and catalytic activity for oxygen reduction, and therefore, have received particular attention recently. La1?xSrxCo1?yFeyO3?δ(LSCF) is a candidate of SOFC cathodes working below 800 °C, considering its high oxygen reduction reaction activity together with its mixed ionic electronic conducting property. Meanwhile, many experimental results pointed out that doping an F anion into the perovskite cathode can improve its electrochemical performance and stability in addition to the conventional A- and B-site doping. To study the oxygen reduction reaction process of the F-doped perovskite cathode, the electronic structure, oxygen absorption on the (100) surface, the formation energy of oxygen vacancy, and activation energies for oxygen ion migration in the bulk F-doped LSCF were calculated based on the density functional theory. The results reveal that doping F in the LSCF can improve oxygen absorption and oxygen ion migration, further promoting the activity of the cathode.
Abstract: Research on high-temperature shape memory alloys has attracted much attention due to the control requirements of the high-temperature drive (>100 ℃) and the overheating warning in high voltage transmissions, nuclear power, aerospace, automotive, oil exploration, and other engineering fields. High-temperature shape memory alloys refer to those with reverse martensitic transformation starting temperature (As) higher than 100 ℃. A wide range of high-temperature shape memory alloys exists, including Ti?Ni?Pd/Pt, Ni?Ti?Hf/Zr, Cu?Al?Ni, Ni?Mn?Ga, Ru-based, β-Ti-based, and Co-based systems. Besides the high transformation temperatures and good mechanical and shape memory properties, the thermal stability of microstructures and properties at high temperatures and after thermal cycling transformations is also an important basis for evaluating the practicability of high-temperature shape memory alloys. Dual-phase Ni?Mn?Ga?Ti high-temperature shape memory alloys were chosen because of their better ductility compared with single-phase Ni?Mn?Ga alloys. In this paper, the as-quenched Ni55Mn25Ga18Ti2 high-temperature shape memory alloy was prepared. Specimens are then thermal-cycled at a temperature between the room temperature and 480 ℃ for 5, 10, 50, 100, and 500 times. The thermal stability of the microstructure, martensitic transformation temperatures, and mechanical and shape memory properties were studied by X-ray diffraction analysis, scanning electron microscopy, simultaneous thermal analyzer, and room-temperature compression analysis. Results show that there are no obvious changes in the phase structure and microstructure of the Ni55Mn25Ga18Ti2 high-temperature shape memory alloy after 500 thermal cycles. All as-quenched and thermal-cycled specimens show dual-phase structures with non-modulated tetragonal martensite and Ni-rich face-centered-cubic γ phase. With the increase of thermal cycling times, the forward martensitic transformation temperatures are almost kept constant, and the reverse martensitic transformation temperatures and the hysteresis are observed to be steady when the thermal cycles exceed five times. After 500 thermal cycles, the compressive strength and compressive stain slightly change, and the shape memory strain drops but remains over 1.4%. The Ni55Mn25Ga18Ti2 high-temperature shape memory alloy shows high thermal cycling stability.
Abstract: Reducing the amount of platinum (Pt) and improving the efficiency of the hydrogen evolution reaction (HER) in alkaline media is a key issue for the industrial production of hydrogen. Unlike HER under acidic conditions, the hydrogen adsorbed-atom (Had) has to be discharged from the water molecule rather than from the hydronium cation (H3O+). Pt catalysts have outstanding H adsorption and desorption free energy but are not conducive to catalyze the dissociation of water, which is the main reason for their hysteresis in alkaline HER. The combination of Pt and a cocatalyst effectively cleave the O–H bonds is an effective strategy to improve the reaction kinetics in the alkaline HER. Currently, in an alkaline electrolyte, non-noble metal hydroxide catalysts are very active for oxygen evolution reaction (OER), especially the Ni–Co hydroxide (NiCoOxHy), which effectively promotes OER owing to its excellent water dissociation ability. In this work, in a three-electrode system, a Pt wire counter electrode was used as the Pt source. Cyclic voltammetry (CV) electrochemical deposition was used to load a trace amount of Pt species onto the NiCo-layered double hydroxides (NiCo-LDHs) prepared using hydrothermal reaction on a nickel foam substrate. NiCo-LDHs can promote the dissociation of water in alkaline media, and Pt sites are beneficial for the binding and desorption of H on the electrode surface. The combination of Pt and NiCo-LDHs effectively paves a new way to enhance the slow kinetics of the hydrogen evolution reaction of Pt in an alkaline medium. The hybrid catalyst Pt?NiCo-LDHs shows considerably improved HER performance, with a small overpotential of 56 mV to drive a typical current density of 10 mA·cm?2 and a low Tafel slope of 43 mV·decade?1 in alkaline media at an ultralow Pt loading of 30.4 g·cm?2. The mass activity of Pt?NiCo-LDHs is 5.6 times higher than that of a commercial Pt/C catalyst with a 100 mV overpotential. Moreover, the Pt?NiCo-LDHs catalyst exhibits outstanding stability after a 100 h test.
Abstract: Lightweight high-temperature titanium alloys are a key material for aero-engines. With the increasing use of new titanium alloys in aero-engines, titanium fire has become a typical catastrophic fault that plagues material design and selection. A burn-resistant titanium alloy is a special material developed to deal with the problem of titanium fire. Its application in aero-engines has become one of the key technologies for the prevention and control of titanium fire. Therefore, explaining the influence of the alloying elements of burn-resistant titanium alloys on mechanical properties is important to provide an important theoretical basis for the design and application of these alloys. Based on the experimental data, the relationship model between the alloying elements and mechanical properties of a burn-resistant titanium alloy was established using a support vector machine algorithm, and the effect of the alloying elements on the mechanical properties was analyzed. The input parameters of the model were V, Al, Si, and C elements, and the output parameters were the room temperature tensile properties (tensile strength, yield strength, elongation, and the reduction of area). Results show that the linear correlation coefficient of each mechanical property of the SVM model is above 0.975, which signifies good prediction ability. The absolute percentage error between the predicted and experimental values of each mechanical property test sample is within 5%, indicating good generalization ability and an effective reflection of the quantitative relationship between the alloying elements and mechanical properties of the burn-resistant titanium alloy for optimizing the composition of the alloy. The mechanical properties of the Ti–35V–15Cr alloy can be improved by adding 0–0.1% Si element and 0.05%–0.125% C element and reducing 2%–5% V element. Meanwhile, the mechanical properties of the Ti–25V–15Cr alloy can be improved by adding 1.5%–1.8% Al element and 0.15%–0.2% C element.
Abstract: Applying fifth-generation mobile communication networks (5G) and time-sensitive networking (TSN) has become a new trend in industrial automation. As the new generation of mobile communication technology, 5G is featured with a large bandwidth, low latency, ultrareliable connection, and multiservice slicing capacities. As the evolution goal of industrial ethernet, TSN is featured with a deterministic transmission with bounded latency and jitter and guaranteed high reliability. Both technologies have been designed to provide converged communication for various services on common network infrastructure. 5G and TSN coordination can effectively promote the integration of Information Technology (IT) and operational technologies (OT), which will be a key enabler of the industrial internet. Therefore, the collaborative transmission of 5G and TSN has become a focus for the industry and academe. “5G + TSN” is envisioned to be the basic communication network for future smart factories, which can integrate various field-level industrial communication technologies and ensure end-to-end industrial data transmission reliability. However, 5G and TSN networks are different in the transmission methods, protocols, control and management mechanisms, etc. How to realize an efficient interconnection and coordination of 5G and TSN is a hot topic and difficult task currently. Following the general requirements of digital, digital-networked, and new-generation intelligent manufacturing, this article first introduced the state-of-the-art of time-sensitive networks, and it also elaborated on the standardization progress of 5G supporting TSN in 3GPP. This work then emphasized the main challenges for the coordinated transmission of 5G and TSN networks and analyzed key technologies such as time synchronization, connection enhancement, and unified resource management to support the coordination of 5G and TSN heterogeneous networks. Finally, the application scenarios of “5G + TSN” in a smart factory were given, aiming to deepen the integration of 5G into industrial control and flourish 5G-based industrial applications.
Abstract: In practical control systems, time delays inevitably occur when sensors need to measure and require the system’s data for decision making as well as when microcontrollers (or other devices) compute and implement control signal processes. The time-delay phenomenon is common in network systems because information (e.g., plant output and control input) is exchanged via a network among control system components and communication delays inevitably arise. Time delays usually affect the dynamic performance of a system, such as the response time and operation accuracy of the system, and may even lead to system instability. Therefore, considering the effects of time delays and effectively compensating for them will improve the performance of a system. Recently, considerable attention has been paid to the study of time-delay problems based on a continuum backstepping control algorithm for its superiority on stability analysis. The design process mainly comprises three steps. First, the original system is transformed into an ordinary differential equation (ODE)–partial differential equation (PDE) or PDE–PDE cascaded system wherein a first-order hyperbolic transport-PDE is introduced to describe the time-delay phenomenon. Thereafter, the cascaded system is turned into a stable system using a Volterra transformation. Finally, a corresponding time-delay compensated control law is developed based on the proposed Volterra transformation. The algorithm based on the continuum backstepping control algorithm is robust, has an inverse optimal control, and exhibits great potential for explicit exact control laws. Moreover, the stability analysis and exact solutions of closed-loop systems are obtained easily. This survey summarizes the basic principle and design procedure of the time-delay compensation method and control law based on the continuum backstepping control algorithm. Further, the recent works of the time-delay compensation control based on this algorithm are introduced for time-delay systems covering the aspects of input, output, and state. Finally, the future works of the time-delay compensation control based on the continuum backstepping control algorithm are discussed.
Abstract: In process industries, the discrimination of final product quality must be implemented in the manufacturing process. At present, the primary method is “after spot test ward,” but there is no other way to realize online automatic discrimination for all products, which frequently leads to customer return purchases and complaints about the product quality, and annual economic loss of 10 billion Yuan in Chinese steel enterprises. This paper proposed online product quality automatic discrimination method based on machine learning to realize online automatic discrimination for all products. First, multidimensional process parameters were mapped into a low-dimensional data set using nonlinear multidimensional parity scaling (MDPS), and the data set is clustered. The distribution feature in the data set was analyzed. The quality index values were then transformed into a low-dimensional map with the class labels determined by process parameter clustering, and the diverse class margins were determined using a support vector machine (SVM) with L2-soft margins. The kernel method set was used to reduce the number of support vectors to simplify the class boundary, and the reduced set determined the actual class margins. Finally, the quality indexes were predicted using machine learning algorithms, such as back-propagation network (BPN), long short-team memory (LSTM), kernel partial least squares (KPLS), and k-nearest neighbors (KNN), including the online automatic discrimination of product quality was realized using the determined class margins and the predicted values of quality indexes. The accuracy of the online automatic discrimination of steel types is up to 97% in the training stage and up to 96% in the testing stage based on industrial production data of interstitial-free (IF) steel.
Abstract: In the past few decades, smartphone-based human activity recognition research has played an important role in many fields, including smart buildings, healthcare, and the military. However, the CPU and storage space of smartphones are very limited, so developing a lightweight human activity recognition learning model has become a research focus and hot spot in this field. To address the abovementioned problems, this paper proposed a lightweight human activity recognition learning model based on the nearest neighbor component analysis (NCA), L2 regularization, and stochastic configuration networks (SCNs). In the proposed model, aiming first at the problem of high dimension and poor separability exhibited by the human activity data, NCA was used to select a subset of highly relevant data from the dataset to improve the lightness of calculation using the learning algorithm in the modeling process and recognition accuracy of the established model. Second, to prevent the occurrence of overfitting when there are too many hidden layer nodes in SCNs, the L2 regularization method was adopted to enhance the generalization ability of SCNs. At the same time, the method of using the supervision mechanism to restrict the generation of hidden layer parameters greatly improved the lightness of the SCNs model. Finally, the proposed learning model and other learning models were verified experimentally on the UCI human activity recognition dataset. Experimental results show that compared with SCNs, the proposed L2?SCNs model reduces the lightness of the number of parameters by 20% and helps improve the accuracy of the model. The introduction of the NCA method has greatly facilitated the recognition accuracy and lightness (modeling time) of the L2?SCNs model, increasing by 3.41% and 70.24%, respectively. Moreover, compared with other state-of-the-art models, such as the support vector machine and long short-term memory network, the proposed model achieves the best recognition accuracy of 97.48% in the shortest time. To sum up, the model proposed herein is a lightweight human activity recognition model with exceptional recognition accuracy and a fast modeling speed.
Abstract: With the increasing popularity of the Internet and the spread of COVID-19, epidemic-related rumors have attracted significant attention, allowing them to brew quickly and pose extremely negative social impacts. It is of great significance to investigate the propagation process of online rumors and offer tentative strategies to curb it. Based on the traditional susceptible, infected, recovered (SIR) model of online rumor propagation, groups of potential and die-hard rumor believers were introduced in this paper, establishing an authoritative rumor-refuting mechanism. Meanwhile, this paper considered factors such as the time-lag effect of rumor refutation from the nonauthoritative and authoritative institutions and the impact of the popularizing rate of higher education on the propagation and refutation of rumors. As a result of the process, the SEIRD (susceptible, exposed, infected, recovered, die-hard-infected) rumor propagation model was established to study how the proportion of the susceptible, exposed, infected, recovered, and die-hard-infected varies under different popularizing rates of higher education, the presence or absence of the authoritative rumor-refuting institutions, and the time-lag effect of rumor refutation. Finally, the model’s effectiveness was verified via experimental simulation, which provided a reference for controlling the spread of online rumor propagation. In addition, the paper proposed a rumor-refuting coefficient to measure the rumor-refuting ability of the nonauthoritative and authoritative institutions. The results show that (1) increasing popularizing rate of higher education significantly slows down the rumor propagation and reduces the rumor propagation peak; (2) refuting the rumors based on the authoritative institutions is decisive for the ultimate elimination of rumors; and (3) eliminating the time-lag effect in refuting rumors facilitates slowing down the propagation of the online rumors. Therefore, the paper puts forward a feasible strategy to eliminate the time-lag effect of online rumor refutation in the future.
Abstract: The liquid water produced by an electrochemical reaction at the cathode of a proton exchange membrane fuel cell blocks the pores in the gas diffusion layer, resulting in “water flooding.” At the same time, membrane dehydration leads to serious ohmic polarization. Discharging liquid water from the stack as soon as possible to ensure the wetting of the proton exchange membrane is a key problem. A membrane humidifier is a key component of a proton exchange membrane fuel cell system for water and thermal management. By considering coupling with the working conditions of a fuel cell, systematic sensitivity simulation analysis of the operating and geometric parameters of the membrane humidifier was carried out. The steady-state mathematical model of the membrane humidifier was established based on Matlab/Simulink. The influences of the inlet mass flow rate, temperature, and pressure, membrane thickness and area on heat transfer, water transfer, relative humidity, and water transfer rate of the membrane humidifier on the wet and dry sides were analyzed. The main conclusions are as follows: Improving the inlet mass flow rate can effectively improve the heat transfer and water transfer quantity, yet reduces the water transfer rate and the relative humidity at the drying side outlet. The increase in temperature on both dry and wet sides can improve the diffusion coefficient and transfer capacity of water in the membrane; however, high temperature significantly increases the saturation pressure of water vapor, reduce water activity, and then reduce the water content of the membrane, which is not conducive for water transfer. The change in pressure has little effect on heat transfer; however, an increase in the total pressure reduces the inlet moisture content and water transfer capacity while increasing the water transfer rate. A larger membrane area and a lower membrane thickness can improve the film moisture transfer and water transfer rates, which can effectively improve the membrane humidifier and fuel cell system hydrothermal management performance.
Abstract: With the aggravation of energy shortage and environmental pollution, the development and utilization of renewable energy have become the focus of research in countries around the world. As a green renewable energy source, offshore wind energy is one of the effective ways to solve these problems. The foundation form of built offshore wind farms is mainly large-diameter monopile. With the development of offshore wind farms expanding toward the deep sea, the applicability of the large-diameter monopile is confronted with some significant challenges. The exploration and research of a new type of foundation are important and meaningful. Affected by the weight of the superstructure and the load of the marine environment, the design of offshore wind turbine foundations should consider the bearing performance of the foundation under vertical load, horizontal load, and bending moment. The ABAQUS software was used to compare the bearing capacities of large-diameter monopile, pile–plate composite foundation, and pile–bucket foundation in saturated clay under vertical load V, horizontal load H, and bending moment M. Results show that the bearing capacities of the two composite foundations are better than the bearing capacities of the monopile foundation. The vertical, horizontal, and bending bearing capacities of pile–plate composite foundations increase exponentially with the increase in the diameter of the plate. The vertical and bending bearing capacities of the pile–bucket foundation increase with the increase in the buried depth of the bucket structure increasing, and the increasing trend gradually weakens parallel to the line. The horizontal bearing capacity of the pile–bucket foundation has a linear relationship with the diameter and buried depth of the bucket structure in the soil. Under the composited loading conditions of V–H and V–M, the failure envelope spaces of the two composite foundations are larger than those of the monopile, and the bearing performance of the two composite foundations is significantly better than that of the monopile.
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
