Ensuring a sustainable supply of mineral resources, while reducing industrial accidents and environmental harm, requires continuous expansion and integration of innovative technologies within the mining sector. These technologies offer significant potential to support the long-term stability of the mineral resource industry. It can enhance resilience to fluctuations in demand, improve operational profitability and reinforce adherence to environmental regulations. Mining 4.0 (M4.0) has emerged as the sector strategic response to rapid digital transformation shaping both mining and associated infrastructure industries. Though, it has been observed that the adoption of M4.0 in developing economies such as India remains challenging. Many mining organisations lack clarity regarding which technologies are most critical and how they should be prioritised for effective implementation. Addressing this gap requires a systematic identification and evaluation of key M4.0 technologies relevant to developing-country contexts. The present study contributes to this need by assessing and ranking the prominent M4.0 technologies applied within Indian coal mining companies through the Decision-Making Trial and Evaluation Laboratory method. The originality of this work lies in the limited number of prior studies focused specifically on prioritising M4.0 technologies in Indian mining sector. Through a literature analysis and expert consultation, 14 core technologies were shortlisted. The results reveal that ‘ Big Data and Analytics’ is perceived as the most influential enabler of digital transformation, whereas ‘ Virtual Reality’ is considered least significant at present. Overall, this study offers actionable insights that can guide Indian mining firms in strategically adopting M4.0 technologies based on their relative significance.
Abstract Lithium–sulfur batteries are expected to supersede existing lithium-ion batteries due to the high theoretical energy density of sulfur cathodes (positive electrodes). Unfortunately, inefficient redox reactions and the “shuttle effect” hinder their commercial development. Assembling high-performance nanostructured sulfur host materials into a sulfur cathode presents a viable solution. However, fabricating host materials and preparing sulfur cathodes involve complicated, multistep, and labor-intensive processes under varying temperatures and conditions, raising concerns about efficiency and cost in practical production. Herein, we propose a single-step laser printing strategy to prepare high-performance integrated sulfur cathodes. During the high-throughput laser-pulse irradiation process, the precursor donor is activated, producing jetting particles that include in-situ synthesized halloysite-based hybrid nanotubes, sulfur, and glucose-derived porous carbon. After laser printing, a composite layer, containing host materials, active materials, and conductive components, is uniformly coated onto a carbon fabric acceptor, forming an integrated sulfur cathode. The laser-printed sulfur cathodes exhibit high reversible capacity and low capacity attenuation during cycling measurements. Furthermore, the laser-printed high-loading samples show high performance in both coin and pouch lithium–sulfur cells. This strategy would simplify the fabrication process in lithium–sulfur battery industry and inspire advancements in other battery research.
The synergistic effect between heterogeneous structures has been proved to enhance the strength and plasticity of alloys, especially in the context of single-phase face-centered cubic (FCC) high-entropy alloys with low stacking fault energy. This study explores the synergistic effects of heterogeneous structures on the strength and plasticity of single-phase FCC FeCoCrNiMo0.2 high-entropy alloys. Through a combination of cryogenic rolling and annealing at 1000 °C for 0.5 h (RA-1000), the alloy demonstrates exceptional strength-ductility synergy and work-hardening ability. The heterogeneous structure comprises fine grains, nano-scale rich- (Cr, Mo) σ phase, and high-density annealing twins. The interaction of σ precipitation and FCC matrix induces heterogeneous deformation-induced strengthening (HDI), while annealing twins and stacking faults act as barriers to dislocation movement, enhancing strength and ductility through a dynamic Hall-Petch effect. Additionally, chemically ordered structures, ordered L12 phase, and type 63 topologically close-packed phases in RA-1000 alloys contribute to improved strain hardening via anti-phase boundaries. This work provides valuable insights for designing multi-scale heterogeneous structures to strengthen high-entropy alloys.
During the coal mining process, the change in the floor stress state of coal seam will produce deformation and failure. The seam floor failure in different coal mining processes has a certain law. At present, the water disaster monitoring of coal seam floors based on the DC resistivity method mainly focuses on the resistivity response characteristics of floor deformation and damage. To investigate the temporal changes in the electrical properties of the coal seam floor during mining, this study employs the inter-hole DC perspective observation system and the time-lapse resistivity reflection coefficient method. Through numerical simulation and field tests, the study uncovers the temporal variation law of the resistivity of coal seam floor induced by mining activities. First, this paper compares the results of individual inversion and time-lapse resistivity change rates for a typical geoelectric model to validate the reliability of the inter-hole DC perspective time-lapse method. Next, considering the mining-induced damage to the coal seam floor, this paper analyzes the electrical response patterns and charac-teristics of the rise of confined water and the damage zone in the floor during the mining process. It also discusses the feasibility of using a time-lapse resistivity reflection coefficient to assess the depth of coal seam floor damage, offering a theoretical basis for field construction. Finally, , the on-site monitoring tests reveal the electrical change characteristics of coal seam floor during the coal mining process. The time-lapse resistivity reflection coefficient R is utilized to determine the damage depth of the rock layer of the working face floor, which is found to be 15 m. The study results demonstrate that the time-lapse characteristics of the resistivity of coal seam floor mining damage obtained by the inter-hole DC perspective method can mitigate the influence of formation factors and random noise in the monitoring data to a certain extent. Additionally, the time-lapse resistivity reflection coefficient can be utilized to determine the depth of coal seam floor failure. This method transforms the detection target from the single study of geological anomalies to the full life cycle dynamic monitoring of the floor damage of the working face in the process of coal mining and then realizes the detailed depiction of structural damage to the working surface floor.
In this work, friction stir welding (FSW) and tungsten inert gas welding (TIG) were applied to prepare two kinds of dissimilar AZ31/AM60 Mg joints. The relationship between mechanical properties, deformation behavior, and microstructure characteristics of both joints was investigated. Microstructural characterization demonstrated that a significant grain orientation fluctuation occurred in the weld zone (WZ) of the FSW joint, but this was not obvious for the TIG joint. Compared with the base metals, the grain size of the FSW joint slightly decreased, but the grain of the TIG joint obviously coarsened. Locally strong texture appeared in the WZ of the FSW joint with a symmetrical distribution, while a random texture character occurred in the TIG joint. Furthermore, the WZ of the TIG joint possessed more and larger second phases than the FSW joint. Tensile tests indicated that both joints had equivalent yield strength (∼120 MPa) and ultimate tensile strength (∼255 MPa), but the elongation (9.0 %) of the FSW joint was lower than that of the TIG joint (12.1%). The similar strength originated from the higher Schmid factors (SFs) of basal slip and extension twinning in the WZ side of the FSW joint and the larger grain size and lower dislocation degree in the heat-affected zone of the TIG joint. The decreased elongation in the FSW joint was due to the apparent inhomogeneous deformation caused by significant SFs (basal slip) fluctuation, while the weaker SFs fluctuation and notable twinning behavior in the TIG joint contributed to the relatively higher elongation.
With the rapid development of intelligent and informationized air battlefields, intelligent air combat has increasingly become key to affecting the outcome of a battlefield. In conventional multi-aircraft air combat, there are issues of low efficiency in intelligent decision-making, difficulty in meeting the needs of complex air combat environments, and unreasonable target allocation. In response to the problems in conventional multi-aircraft air combat, we introduce a long short-term memory–proximal policy optimization algorithm (LSTM–PPO). Using the long short-term memory network to extract features and perceive the situation of the state, an intelligent agent trains the normalized and feature-fused state information residual network and value network, chooses the optimal action through the proximal policy optimization strategy based on the current situation, and embeds a reward function containing expert knowledge during the training process to solve the problem of sparse rewards. Meanwhile, a target allocation algorithm based on threat value calculation is presented. Using angle, speed, and height threat values as the basis for target allocation, the ID of the target aircraft with the highest threat value on the battlefield is calculated in real-time. When the strategy network outputs an action of attack, it conducts target allocation. To confirm the effectiveness of the algorithm, we carried out 4v4 multi-aircraft air combat experiments in a digital twin simulation environment built by our research group. The red team consists of reinforcement learning agents based on LSTM–PPO algorithm, whereas the blue team comprises a finite state machine composed of expert knowledge bases. After more than 1200 rounds of aerial confrontation, the algorithm has been converged, and the win rate of the red team has reached 82%. Furthermore, we assessed the performance of four other mainstream reinforcement learning algorithms in 4v4 air combat experiments under the same experimental conditions. It is shown that the deep Q-network (DQN) and soft actor-critic (SAC) algorithms have difficulties in dealing with high-dimensional continuous action spaces and multiagent collaboration. The multi-agent deep deterministic policy gradient algorithm (MADDPG) employs a multi-agent strategy and cooperative training, so it exhibits a significantly higher win rate than the DQN and SAC algorithms. The multi-agent proximal policy optimization (MAPPO) algorithm has a relatively high failure rate and is not stable enough to deal with enemy aircraft’s strategies in some cases. The LSTM–PPO algorithm shows a significantly higher win rate than other mainstream reinforcement learning algorithms in multi-aircraft collaborative air combat, which confirms the effectiveness of the LSTM–PPO algorithm in dealing with high-dimensional continuous action spaces and multi-aircraft collaborative operations.
The effects of hydrostatic pressure on grain refinement and deformation behaviors of Mg–13Gd–4Y–2Zn–0.5Zr alloy were investigated. With the increase of hydrostatic pressure, the equivalent stress and forming load increase, and stress triaxiality also increases. The hydrostatic pressure has little effect on dynamic recrystallization (DRX) fraction and grain size, and the DRX fraction difference is not greater than 10%. This is because DRX critical strain and grain nucleation are almost unaffected by hydrostatic pressure. The slight increase in DRX fraction under higher hydrostatic pressure is attributed to the enhanced <a> dislocation activity near the lamellar long-period stacking ordered (LPSO) phase and significant local temperature elevation in the deformation zone. The high hydrostatic pressure is mainly borne by the LPSO phase. The bending deformation energy of the lamellar LPSO phase increases with the increase of hydrostatic pressure. The area fraction of samples is decreased from 18.5% of one direction compression & simple shear (1-CS) sample to 13.6% of three directions compression & simple shear (3-CS) sample. The solute diffusion and deconstruction of the bulk LPSO phase occur at higher hydrostatic pressure. The hydrostatic pressure has little effect on the basal texture strength of α-Mg phase under strong shear stress. The activation of <c+a> dislocation, as the primary source of non-basal slip, shows the same distribution characteristics.
The two-sheet hollow structure of the 1420 Al-Li alloy was prepared by the method of superplastic forming and diffusion bonding. The interface combination status of the diffusion bonding region and the microstructure of the superplastic forming region were observed by an optical microscope. The thickness distribution of the superplastic forming region was measured by an ultrasonic thickness meter machine, the defect detection was tested by X-ray nondestructive inspection, and the failure modes of the samples were analyzed. The results showed that the two-sheet hollow structure of the 1420 Al-Li alloy was prepared successfully, the structure was integrated, and there were no shape defects such as pit, wrinkle, and collapse. The structure shape was almost attached to the die completely, and the thickness was almost uniform distribution. The no deforming area of the two-sheet hollow structure of the 1420 Al-Li alloy was a long strip, rolled microstructure, while the grains near the round corner area were equiaxed states resulting from dynamic recrystallization. The improper control of the superplastic gas pressure in the forming process would lead to the tearing or the die-attaching failure for the two-sheet hollow structure of the 1420 Al-Li alloy.
Seungyeop Baek, Gun Yung Go, Jong-Wook Park
et al.
The present study investigates a fatigue property and its microstructural and interface geometrical effect on the resistance element welded (REWed) aluminum (Al)/high-strength steel (Fe) lap joint. The assembled Al/Fe joints were subjected under the fatigue strength up to 80% of tensile-shear loads with 0.1 of the load ratio. As a result, an exceptional fatigue strength has been secured inducing the base material fracture because there are no noticeable interfacial defects at the 10.5 kA welding condition compared to assemblies joined with 3.5–4.5 kA of welding currents. Even, maximum tensile-shear loads exceed 9 kN at the 10.5 kA welding condition. Microstructural developments of base materials and welding interfaces were thoroughly analyzed by an optical microscopy (OM) and electron backscatter diffraction (EBSD), the development of prior-austenite-grain-boundaries (PAGBs) and α'-martensite phases were observed in the welding interfaces at all conditions. Heat affected zone (HAZ) developments of AA5052 were quantitatively analyzed in terms of recrystallization and grain growth, providing significant differences in the fatigue performances and striation, crack propagation developments. In addition, with the help of a finite element (FE) computational modeling, a mechanical stress distribution and strain behavior by geometries of the joining interface are discussed in detail.
To obtain the high performance solid spherical molybdenum powder raw materials, the spherical molybdenum powders were prepared by the pulse laser wire cutting. The particle size, morphology, microstructure, and other physical properties of the molybdenum powders were studied by sieving, optical microscope, and scanning electron microscope, respectively. The results show that the morphology of molybdenum powders prepared by the pulse laser wire cutting is spherical or nearly spherical, and the surface is smooth without the satellite particles or particle aggregation. In the range of the experimental process parameters, more than 90% molybdenum powder particles are over 150 µm in size, and the particles in the range of 150~300 µm account for the largest proportion, more than 60%. Molybdenum particles with the particle size less than 400 µm are usually internally dense, while the internal holes appear in some larger particles. The formation mechanism of molybdenum particles and internal holes is preliminarily analyzed.
AbstractTailings transport system design is generally based on identifying the minimum and maximum process boundary conditions for pump selection and pipeline sizing. The approach is robust and well-proven. However, the approach has the potential to skew selections to operating scenarios that have a very low likelihood of occurring, such as the combination of high solids throughput and low tailings solids concentration. The approach can result in a tailings transport system design that is overly conservative. A probabilistic method-based approach captures the independent variability of design inputs and the combined likelihood of outcomes. This approach identifies the process conditions that have the highest likelihood of occurrence and are most applicable to equipment and pipeline selections. An outline of a probabilistic-based approach to tailings transport system design and the resulting selections is provided in this article. The probabilistic-based system design is compared to the outcomes from the traditional approach. The benefits and challenges to this approach are discussed and recommendations for utilizing this approach for tailings transport system design are provided.
Coal mine gas and coal dust explosion will produce explosive sound. Coal and gas outburst will produce the sound of coal cannon and the supports will produce squeaking and cracking sound. Rock burst will produce huge rock breaking sound and vibrations. Coal mine water inrush will produce 'hissing' water sound, and a large amount of water inrush will produce water flow sound. Coal mine roof fall will produce roof cracking sound, coal rock hitting the ground sound and support damage sound. According to the characteristics of the sound of extraordinary accidents in coal mines, the alarm methods of accidents of mine gas and coal dust explosion, coal and gas outburst, rock burst, water inrush and roof fall are proposed. The characteristics of the time domain and frequency domain of each accident sound are different from the characteristics of other sounds, and the sound can be monitored in real time by mine explosion-proof sound pickup equipment and system. Therefore, accidents can be sensed and alarmed through the intelligent analysis of the sound and the analysis of the characteristic parameters of the sound frequency, amplitude and short-term energy. By monitoring and analyzing the sound intensity and other characteristics of different monitoring locations, the sequence of occurrence and the damage sequence of explosion-proof sound pickup equipment, the accident location is able to be determined. Based on the characteristics of each accident, the accident identification method of multi-information fusion analysis is proposed to reduce the sound interference of coal fall from the working face, blasting operations, coal mining equipment, excavation equipment, transportation and lifting equipment, power supply equipment, emulsion pumps, water pumps and local ventilators. The paper discusses the advantages and disadvantages of different sound pickup equipment and proposes that the microphone arrays should be used for mine sound pickup equipment. Furthermore, the paper proposes a sound recognition classifier applicable to coal mine extraordinary accidents.