Abstract: Grinding is an important link in the process of mineral processing. This is because whether the useful minerals in the ore can fully dissociate the monomers and the particle size meets the sorting requirements have a decisive effect on the beneficiation index. Over the last two decades, the discrete element method (DEM) has become an important tool for understanding comminution fundamentals and providing theoretical guidance for the design, optimization, and operation of comminution devices. DEM is now widely used in industries where comminution is critical. The application of DEM in simulating fracture, breakage, crushing, milling and equipment wear has become increasingly extensive and complex, resulting in tremendous changes in the understanding of the grinding process. In this article, the application background of DEM in the field of grinding was introduced; the basic principles of two commonly used models in DEM, the Hertz-Mindlin contact model, and the bonding particle model, were explained. Subsequently, the application status of DEM in ball mills, stirring mills and self-mill/semi-automatic mills, and other three types of grinding equipment and parameter optimization research were summarized. Finally, it further pointed out the unique advantages of DEM in the field of grinding and its development direction.
Abstract: Compared with other production industries, metal mine is recognized as a high accident rate and the highest casualty rate due to the bad working environment. Therefore, safety production is the key concern of mining enterprises. With the attention of enterprises to safety problems and the increasing improvement of mine safety management system, many mines have established secure big data platform to effectively manage production and ensure the safety of underground operation, receiving the safety hazard information from daily safety inspection into the platform. However, due to the data of security risks are unstructured short texts with the operation of the enterprise, including the data recorded in the platform presents the characteristics of complex data content, large data scale, and non-standard data records. Moreover, due to the lack of an effective text analysis model, a small part of the security risk data is only used for simple analysis such as report analysis and data statistics, whereas more data is stored in a secure big data platform. Thus, the data did not play a guiding role in production, resulting in a waste of these valuable data resources. In order to explore the internal relationship between hidden danger data and the rule of hidden danger occurrence, based on big data analysis technology, this paper constructed a multi-dimensional analysis model of mine safety hidden danger. We analyzed the distribution law of hidden danger in two dimensions of time and space, used the topic mining model to classify hidden danger information, and obtained 13 hidden danger topics, using association rules to mine hidden danger. The model explores the internal relationship between different hidden dangers and uses an R programming language to visualize the above results. The results made full use of the mine hidden danger data and avoided the waste of data resources through the analysis and research of the hidden danger with a certain guiding value for preventing mine accidents.
Abstract: The gas composition of spontaneous coal combustion in a high-temperature mine fire area is extremely complex. Due to the low-temperature oxidation or pyrolysis of coal, a variety of combustible and explosive gases are produced, such as CH4, CO, H2, C2H6, C2H4, C3H8, and C2H2. The paper provided associated basic data to quantify potential hazards caused by flammable gases and design containers that can withstand explosion during gas fuel processing, storage, and transportation. Under different initial temperatures (298–373 K) and varying volume fractions of the premixed gases (CO, H2, C2H4, and C2H6: 0.4%–2.0%), when volume fraction of methane is 7% and 11%, the explosion pressure characteristic parameters were obtained in a 20 L spherical gas explosion system. In addition, the change in trend of the mole fraction of H·, O·, and OH radicals of the gas mixture during the explosion process was analyzed and simulated. Sensitivity analysis was performed using the CHEMKIN software. Results show that at the same volume fractions of the premixed gases, the maximum explosion pressure linearly decreases with increasing initial temperature and the maximum pressure rise rate is almost constant or slightly decreasing. At the same initial temperature, when volume fraction of methane is 7%, as the volume fractions of the premixed gases increases to 2%, the maximum explosion pressure and the maximum pressure rise rate show an increasing trend. However, a decreasing trend is observed with 11% methane–air mixture. When volume fraction of methane is 7%, with the increased gas mixture volume fraction, the maximum mole fraction of the free radicals, H·, O·, and ·OH increases. When volume fraction of methane is 11%, the maximum mole fraction of O· and ·OH radicals indicated a downward trend, whereas that of the H· radical increases with increase in volume fractions of the premixed gases. When volume fraction of methane is 7% and 11%, chemical kinetics analysis revealed that the addition of premixed gases had little effect on the key elementary reactions. Moreover, the sensitivity coefficient of CH4 decreases with increase in volume fractions of the premixed gases.
Abstract: As an unconventional natural gas resource, coalbed methane has huge reserves in China and has good prospects for exploitation. During the coalbed methane extraction process, a large amount of coal powder is produced. Coal powder accumulates in fissures and blocks them, which is one of the important factors affecting the permeability of coalbed methane. A hydraulic fracturing system with adjustable frequency pulsation and single-slit filling prefabricated samples were developed for testing coalbed fissure unblocking. Experiments were carried out to study the evolution process of the unblocking pressure and the unblocking effect of pulse action under different frequency conditions. Results show that the evolution process of the unblocking pressure can be divided into three stages: pressure rise phase, decline phase, and pressure fluctuation stability phase. Compared to that, under a steady flow, the pressure threshold under the pulse action is lower, pressure drop duration is shorter, and pressure drop amplitude is smaller. The migration of pulverized coal under the action of steady flow is concentrated in the pressure drop stage. Under the action of pulsating pressure, pulverized coal migrates in the pressure drop stage and the pressure fluctuation stable stage. The pressure drop time is positively correlated with the total amount of pulverized coal transported, but the total transport volume of pulverized coal is equivalent to that under the action of steady flow. The fluid infiltration along the radial direction mainly occurs during the pressure rise to the peak pressure. The filtrate penetration radius is smaller due to the shorter unblocking time under the pulsating flow, and the reservoir damage is small. Comprehensively considering the unblocking pressure, coal migration, unblocking seepage path, and unblocking seepage depth, especially the unblocking pressure and unblocking seepage depth, as the main evaluation factors, the best unblocking effect is under the condition of 3 Hz, which has a lower solution.
Abstract: Due to the high crack sensitivity of non-quenched and tempered steel and the difficulty of accurate control of secondary cooling, surface cracks of the continuous casting strand occur frequently. A secondary cooling control method based on the solidification characteristics of non-quenched and tempered steel was proposed. For the solidification characteristics, the effect of the cooling rate on the secondary phase precipitation was studied using a confocal microscope and field emission scanning electron microscopy (FESEM), and the phase transformation mechanism of proeutectoid ferrite was clarified. Results show that the second-phase particles start to precipitate at 1086 °C and reach a peak at ~912 °C. When the cooling rate ranges from 0.1 to 5 °C·s?1, the size and volume fraction of the second-phase particles decrease with the increase of the cooling rate, and the second-phase particles transition from a chain-like distribution at the grain boundaries to a uniform distribution in the matrix. Increasing the cooling rate is helpful to weaken the pinning effect of the precipitates and strengthen the microstructure of the bloom surface. As for the secondary cooling optimization, a heat transfer and solidification model considering a transverse water distribution was established, and a secondary cooling optimization method based on the solidification characteristics of non-quenched and tempered steel was proposed. Strong cooling is performed after the strand leaves the mold to meet the requirements of a reasonable cooling rate and temperature range for controlling the precipitation of particles. Industrial trials confirm the feasibility of the technical solution. In addition, the study shows that reducing the spray distance can improve the transverse non-uniformity of secondary cooling water. In this study, the influence of the secondary cooling water amount and spray distance on the crack sensitivity of non-quenched and tempered steel was comprehensively considered, and the secondary cooling process was optimized by studying the “longitudinal?transverse” solidification cooling. The proposed optimization scheme contributes to the improvement of surface and subsurface cracks of continuous casting bloom.
Abstract: With the rapid development of new energy vehicles and the energy storage industry, traditional cathode materials often do not meet people’s expectations of high energy output and high density for lithium-ion batteries. The layered oxide xLi2MnO3·(1?x)LiMO2 (M=Ni, Mn, Co), rich in Li and Mn, is expected to be an ideal anodic material for the next generation of lithium-ion batteries owing to its high specific capacity exceeding 250 mA·h·g?1. However, the Li-rich materials still suffer from high irreversible capacity loss at the first cycle, poor cycle performance, and inferior rate capacity. The voltage decay mechanism of lithium-rich manganese-based cathode materials involves factors such as surface phase transition, anion redox, transition metal migration, and oxygen release. As a commonly used modification method, the coating can effectively solve these problems. At present, the coating modification mechanism of cathode materials mainly includes the following three types. (1) Surface coatings can reduce the direct contact between lithium-rich materials and electrolytes. They stabilize the interface, prevent excessive metal dissolution, and effectively prevent the surface structure of the active material from collapsing. (2) Surface coatings can reduce oxygen activity, improve irreversible oxygen loss, inhibit solid electrolyte interphase (SEI) film growth, and improve material thermal stability. (3) Surface coatings can improve the conductivity of the positive electrode active material, which builds a conductive network on the surface to provide a fast transmission channel for electrons and lithium ions. Surface modification can optimize the surface and structure of the lithium-rich layered material, and the modified material shows a higher discharge capacity and good cycle stability, with superior rate performance and thermal stability. This paper expounded upon the lithium-rich cathode material structure and electrochemical reaction between the structure–activity relationship and discussed the influence of metal oxides, metal fluoride, carbon, conductive polymer, and lithium-ion conductors on the coating material, the electrochemical performance of lithium-ion battery cathode materials, and the mechanism of action. We also summarized the advantages and disadvantages of the abovementioned coating in the application of lithium-ion battery cathode materials. Finally, future developments in the coating modification of lithium-rich cathode materials for lithium-ion batteries were discussed.
Abstract: With increasingly serious energy shortages and environmental pollution, electric vehicles (EVs) have drawn widespread attention in recent years. The lithium-ion battery is widely used in the field of EVs owing to its superior energy density, life cycle, low self-discharge rate, and maintenance of memory. Prediction of the remaining useful life (RUL) of lithium-ion batteries is a key parameter in battery management systems. The accurate prediction of RUL is a prerequisite to ensuring the safety and reliability of the battery system. The gradual deterioration in the performance of lithium-ion batteries with cycling is normally predicted using capacity and resistance. However, this method is difficult to use in practical applications. To address this problem, a nonlinear autoregressive model with exogenous inputs (NARX) dynamic neural network was proposed to predict RUL. First, according to the discharge data of the lithium-ion battery, three indirect health indicators, namely, cut-off time, constant current time, and peak temperature time in discharge, were proposed, and grey relation analysis (GRA) was used to analyze their relation to capacity. The proposed three indirect health indicators have significant relationships with battery capacity. In addition, due to the influence of temperature vibration, electromagnetic interference, and external disturbance, RUL prediction of the lithium-ion battery is a typical nonlinear problem. In order to cover this weakness, the NARX dynamic neural network was established to predict the RUL of the lithium-ion battery. Finally, a closed-loop and an open-loop NARX were compared with the backpropagation neural network based on particle swarm optimization (BPNN-PSO), least-square support vector machine (LS-SVM), and extreme learning machine (ELM) of existing models under the open data of NASA. The experimental results show that the estimation performance RMSE (NO.5) of the proposed model is improved by about 33% compared with the standard ELM, verifying that the proposed model is superior to other methods in the RUL of lithium-ion batteries.
Abstract: As a new type of magnetic sensitivity smart material, magnetorheological elastomers showing a good magnetorheological effect have been broadly applied in the field of intelligent structures and devices. A viscoelastic fractional derivative element was introduced into the stress?strain relationship of magnetorheological elastomers based on the Bouc?Wen model to accurately characterize the mechanical behavior of magnetorheological elastomers under a wide range of strain amplitude, excitation frequency, and magnetic field and to make it better applied in engineering practice. Further, a modified Bouc?Wen model based on a fractional derivative was proposed to describe the hysteresis characteristics of magnetorheological elastomers. The Bouc?Wen model has good universality and can accurately describe the hysteretic characteristics of the magnetorheological elastomer’s nonlinear viscoelastic region, but it cannot accurately simulate magneto-viscoelasticity and frequency dependence. The fractional derivative can express this characteristic with fewer parameters and higher accuracy. The micromorphology characteristics of isotropic and anisotropic magnetorheological elastomers were analyzed, and the performance tests of the magnetorheological elastomers were conducted. The storage and loss modulus of the magnetorheological elastomers initially remain unchanged and then decrease with an increase in strain amplitude (0–100%). Moreover, the storage and loss modulus of the magnetorheological elastomers increase with an increase in frequency (0–100 Hz) and magnetic flux density (0–545 mT). On this basis, a modified Bouc?Wen model was proposed based on the fractional derivative. The simulation model was established using the Simulink software, and the fractional derivative part of the modified model was approximately calculated using the Oustaloup filter algorithm. The effectiveness of the modified model was verified through a comparative analysis. The fitness values of simulation and experimental data under different loading conditions are higher than 98%. Results show that the modified Bouc?Wen model can accurately simulate the stress?strain hysteresis loops of the magnetorheological elastomers, and the fitting accuracy is significantly improved compared with that of the Bouc?Wen model. The modified model is accurate and effective in a wide range of strain amplitudes, frequencies, and magnetic fields, which can lay a foundation for the engineering application of magnetorheological elastomers.
Abstract: Evolutionary game theory involves multiple disciplinary sciences and has enormous scientific value and promising applicability. Collective behavior is an important topic of interdisciplinary study. Ethology has shown the ubiquity of collective behavior and has proven the rationality of evolutionary theory in explaining the emergence of collective behavior. The recent development of complex network theory offers a convenient framework for describing game interactions and competition relationships among individuals. The combination of evolutionary games and complex networks, particularly, evolutionary game theory in a complex network, has been attracting growing interest from different fields. It has undergone substantial development, especially in quantitative analysis of two-strategy competition. Under this framework, the complex network represents the population structure, and the game describes interactions between individuals. On the basis of the methodology from network science, stochastic process, and statistical physics, the framework mainly focuses on how population structures, individual behavior patterns, and interacting environments influence the emergence of collective behavior. In this paper, the mechanisms for the evolution of cooperation were given under the framework of evolutionary game, including kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. Recently, the effects of individual heterogeneity and environmental feedback on cooperation had attracted growing interest. Next, five main theoretical methods were addressed for analyzing the evolutionary game in complex networks, including the $ \sigma $- dominance rule, the coalescing theory, the pairwise approximation, the coalescing random walk theory, and the adaptive dynamics. Particularly, the recently proposed coalescing random walk theory is suitable for analyzing the dynamics of any network structure and any update rule. Then, the studies on the evolution of fairness in ultimatum games were presented, and reasonable resource allocation is the key factor for social stability, economic development, and individual health. Finally, the challenges and further directions of studying ultimatum games in a complex network were summarized.
Abstract: With the widespread popularity of network-based techniques and extension of computer control scales, more dynamical systems, particularly complex nonlinear dynamics, including increasing communication burdens, increasing difficulties in building accurate mathematical models, and different uncertain factors are encountered. Consequently, in contrast to the linear case, the optimization of the design of these uncertain complex systems is difficult to achieve. By combining reinforcement learning, neural networks, and dynamic programming, the adaptive critic method is regarded as an advanced approach to address intelligent control problems. The adaptive critic method has been currently used to solve the optimal regulation, trajectory tracking, robust control, disturbance attenuation, and zero-sum game problems. It has been considered a promising direction within the artificial intelligence field. However, many traditional design processes of the adaptive critic method are conducted based on the time-based mechanism, where the control signals are updated at each time step. Thus, the related control efficiencies are often low, which results in poor performance when considering practical updating times. Hence, more improvements are needed to enhance the control efficiency of adaptive-critic-based nonlinear control design. In this study, we developed an event-based iterative neural control framework for discrete-time nonlinear dynamics. The iterative adaptive critic method was combined with the event-driven mechanism to address the approximate optimal regulation problem in discrete-time nonlinear plants. An event-triggered value learning strategy was established with two iterative sequences. The convergence analysis of the iterative algorithm and the neural network implementation of the new framework were presented in detail. Therein, the heuristic dynamic programming technique was employed under the event-based iterative environment. Moreover, the triggering condition of the event-driven approach was determined with the appropriate threshold. Finally, simulation examples were provided to illustrate the excellent control performance, particularly in utilizing the communication resource. Thus, constructing a class of intelligent control systems based on the event-based mechanism will be helpful.
Abstract: Quadruped bionic robots are favored by development experts because of their broad application prospects, such as interstellar exploration, educational companionship, and social inspections. Quadruped robots were developed and inspired by mammals, which are known to exist in most areas on the earth's land surface. However, quadruped robots cannot achieve such an ideal state due to various reasons. At present, the adaptive problem of quadruped robots under a complex and changeable terrain has made significant progress, as reported in related literature. However, the case of robots that are as flexible as mammals in nature and meet the needs of multi-functional and multi-scenarios are still poorly understood. A quadruped robot is prone to posture instability when dynamically traveling in a ground environment with variable rigidity. This work proposes a real-time adjustment strategy of the active variable stiffness of the legs. This strategy estimates the landing in real time based on the motion state of the fuselage and legs after the robot touches the ground. The coupling stiffness of the legs and the ground and the difference between the coupling stiffness of the front and rear legs and the ground is compensated to the corresponding landing legs. This enables the robot to quickly adapt to the ground with different stiffness characteristics after landing, especially when the ground stiffness differs greatly. The Simulink-SimMechanics simulation platform is established with the diagonal legs on the same stiffness ground and on different ground environments with variable stiffness. The active leg stiffness adjustment strategy combined with conventional attitude feedback control is tested, and results are compared with those using only a conventional attitude feedback control. Results show that through the active variable stiffness of the legs, the quadruped robot realizes the compensation and correction of the pitch and roll angle of the fuselage during the transition between soft and hard ground. Moreover, the control effect is better than that of the conventional attitude feedback control alone.
Abstract: With the growth in energy demand, shale gas has attracted considerable attention as an unconventional clean and efficient energy source. In addition, the recoverable reserves of deep shale gas in China far exceed those with a depth less than 3500 m. Thus, deep shale gas is an important replacement field for shale gas production in China. Shale, as a shale gas reservoir, forms many weak surfaces in the deposition process and shows different degrees of anisotropy in the mechanical properties. Therefore, it is of great importance to use particle flow code (PFC) to explore anisotropy of shale from the perspective of micro-level for deep shale gas production in China. Based on the experimental results obtained from the shale specimens under conventional triaxial compression, PFC2D was used to simulate the triaxial mechanical properties of shale with different bedding inclinations. The effects of bedding inclination and confining pressure on the mechanical properties of shale specimens were analyzed. The following results are obtained. (1) With the increase of bedding inclination, the peak strength and cohesion of shale all display a "U"-type variation, but the trend of peak strength is different under different confining pressures and the internal friction angle varied nonlinearly with the bedding inclination increases. (2) The effects of bedding inclinations on the displacement direction and size of surrounding particles decrease with the increase of the angle between the bedding inclination and axial stress. (3) At constant bedding inclination, the number of microcracks at the final failure of the specimen increases with the increase of confining pressure. Under the same confining pressure, the number of microcracks in the final failure of the specimen first decreases and then increases with the increase in bedding inclination. (4) With increased confining pressure, the brittleness of shale with the same bedding angle decreases as a whole. Under low confining pressure, shale brittleness is larger at both ends and smaller in the middle with the increased bedding inclinations.
Abstract: Loess is widely distributed in the Northwest Plateau of China. One-third of the landslides in China occur in the loess area. Shallow loess landslides are especially widespread and frequent geological disasters, causing serious casualties and huge property damage. Under rainfall and loading, loess is prone to structural collapse and strength reduction. Therefore, shallow loess landslides distribute widely and occur frequently. Usually, rainfall and earthquakes are the frequent and active triggers for loess landslides. In recent years, a large number of loess landslides have been induced by the coupling of rainfall and earthquakes on the Loess Plateau. Although the coupling effect of earthquake and rainfall will seriously aggravate the instability probability and disaster risk of shallow loess landslides, there is still a lack of quantitative disaster evaluation research on such landslide events. This study chose the shallow loess landslide as the research object in the Dashagou catchment of Lanzhou city. The rainfall penetration model was integrated into a three-dimensional deterministic model of the loess slope, and the stability of the shallow loess landslide was evaluated in the study area with different rainfall and seismic coupling effects. The confusion matrix and the receiver operating characteristic (ROC) curve were used to evaluate the results of the stability evaluation prediction. Results of this study reveal that the integration of a three-dimensional deterministic model of rainfall infiltration and earthquake effects has a good impact on the stability evaluation of shallow loess landslides at the watershed scale. Moreover, this model can be used as a tool for the assessment and early warning of rainfall and earthquake-induced loess landslides. The employment of the three-dimensional deterministic model considering a complicated slope and rainfall situation has great significance in the acquisition of results that are more accordant with the actual situation. It is of great reference value to strengthen the spatiotemporal disaster assessment and prediction of loess landslide disasters under different scales of extreme events.
Abstract: When a shale oil reservoir contains a mass of clay minerals, the salinity of formation water can reach up to 4.786×103 mol·m?3 and the formation water and low salinity fracturing fluid create significant osmotic pressure during the fracturing process. To investigate the effect of osmotic pressure on the imbibition effect, a two-dimensional, oil-water, two-phase, discrete fracture network model was established. This model comprehensively considers osmotic pressure and capillary force. Additionally, a series of studies were carried out to explore the influence of osmotic pressure, capillary force, shut-in time, salt concentration, membrane efficiency, and the proportion of branch fracture area on the imbibition effect in shale oil reservoirs during fracturing fluid pumping and shut-in. The results show that: (1) Filtration is mainly influenced by pressure difference, capillary force, and osmotic pressure, and pressure difference is the key control mechanism of filtration. (2) The shut-in time has a great influence on the imbibition effect of fracturing fluid. The imbibition amount in the first 15 d can reach 80% of the total imbibition amount when the well is shut in for 50 d, leading to the shut-in pressure spreading to the fracturing interval on either side. (3) Osmotic pressure takes longer to reach equilibrium than diffusion pressure. Osmotic pressure takes 50 d to shut in the well and make the salinity near the fracture reach 600 mol·m?3 when the salinity of local layer water is 4.786×103 mol·m?3. (4) As pressure difference is the main factor that affects the imbibition effect and the effect of shale film efficiency on seepage pressure diffusion is weak, the extent of imbibition increases by only 4% when the shale film efficiency increases from 5% to 30%. (5) Water saturation is controlled using hydraulic fractures through small spacing during shut-in, and the influence of branch fractures on water saturation is limited in intensive volume fracturing to horizontal wells.
Abstract: A dam is an important piece of infrastructure for ensuring economic and social development. During operation, because of environmental changes, aging materials, and other factors, a dam may develop accident risks and once it fails, it poses a great threat to society. Therefore, it is of great significance to use reasonable methods for analyzing the monitoring data collected by a dam safety monitoring system and evaluate a dam’s behavior to ensure operation safety. At present, the existing methods are mainly devoted to evaluating the local state of a dam according to the monitoring information of a single measuring point. Relatively few studies are available on the evaluation methods for the overall state of a dam, and the existing methods are mainly qualitative and subjective. To address this problem, the residual between the model calculated value and the measured value was taken as the research basis. The concept of the fusion residual, an important index for characterizing the overall behavior of a dam, was promoted. Combined with the information entropy theory, the variation of residuals at different measuring points was studied, and the fusion weight of residuals at each measuring point was analyzed. The fusion residual was calculated. Based on the distribution analysis of the fusion residual, a concept cloud representing the different states of a dam, namely, the evaluation criteria, was established using a reverse cloud generator and a forward cloud generator. On this basis, an evaluation model of the overall behavior of a dam was established and combined with the cloud similarity algorithm. The example shows that the evaluation method can effectively identify the abnormal value of a dam and evaluate its overall behavior. The evaluation results are reasonable and reliable. The model can evaluate the overall behavior of a dam quantitatively and objectively, and the evaluation results are reasonable and reliable, providing an important reference for the safe operation of a dam.
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
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