Abstract: The real-time inline monitoring technologies of focused beam reflectance measurement (FBRM) and particle video microscopy (PVM) were used to analyze the aggregate structure evolution during the operation of a dynamic thickening system. The tailings dewatering studies were performed under two series of conditions: (i) rake rotation speeds of 0, 0.1, 1, and 10 r·min?1 and an initial mud bed height of 75 cm and (ii) initial mud bed heights of 75, 45, and 25 cm and a rake rotation speed of 0.1 r·min?1. The aggregate diameter, particle size distribution, and real-time images of the tailings thickening process were obtained. The results show that with the increase in the shearing time, the diameter and counts of aggregate first increase, then decrease, and then become stable. According to the aggregate diameter variation, the aggregate evolution can be divided into three stages: growth, reconstruction, and densification periods. The condition of a shear rate of 0.1 r·min?1 and an initial mud bed height of 75 cm has the best effects on the aggregate growth, structure breaking acceleration, aggregate reconstruction, and aggregate densification improvement, as determined in the laboratory; however, high shear rate has a degrading effect on the aggregate structure evolution. The aggregate diameter progressively decreases with the increase in the shear rate. The longer the aggregate growth period, the larger the maximum aggregate diameter, and a longer reconstruction period is observed at higher initial mud bed heights. Moreover, the aggregate diameter increases with the increase in the initial mud bed height. The fractal dimension of tailings aggregate reflects the change characteristics of the aggregate structure. According to the calculation of fractal dimension and porosity of the PVM image, the dynamic equilibrium relastionship between the breaking force and cohesive force of aggregates was analyzed, the influence on the aggregate breaking was analyzed. The aggregate densification rule in the tailings thickening process was revealed analyzed, based on the dynamic equilibrium relationship between the breaking force and cohesive force of aggregates.
Abstract: The in-situ utilization of lunar mineral resources is fundamental process for the establishment of a lunar base and subsequent exploration of deep space. However, the special environment of the moon and the cost of earth–moon transportation limit the direct application of existing mining and metallurgy technologies to achieve the in-situ utilization of lunar regolith. Since the 1980s, when NASA first proposed the “In-situ Resource Utilization” program (ISRU) and began to put it into practice, scientific researchers from all over the world have carried out fruitful research on the orientation of the in-situ utilization of lunar mineral resources and developed several technologies with great application potential. These methods can be divided into materialized molding and extractive metallurgy. Materialized molding processes, such as the sintering method and 3D additive manufacturing method, are mainly used to directly materialize the lunar soil to prepare building materials for the lunar base. Meanwhile, metallurgical extraction processes include carbon/hydrogenation medium reduction, electrolytic reduction, and vacuum pyrolysis, which can produce the corresponding metal or its suboxides and oxygen. At present, the main raw materials used in related engineering applications and ISRU research are lunar soil simulants. This paper briefly summarized the special space environment of the moon and its influence. Moreover, the characteristics and applications of lunar soil simulants synthesized in different countries were compared. The main steps, technological characteristics, research status, and application prospects of lunar soil and lunar soil simulant’s materialized molding process were then introduced. This work also summarized the general principles, basic processes, thermodynamics, and kinetics of the lunar soil’s in-situ extraction metallurgical technology, as well as the latest research progress. Finally, the advantages and disadvantages of these methods were discussed, and their applications in the in-situ utilization of lunar minerals were proposed. In addition, the possible impact of the special lunar environment on the implementation of related technologies and products in the future was discussed and prospected.
Abstract: Titanium is widely used in the manufacture of stainless steel due to its stabilizing ability of carbon and nitrogen, the pinning effect on grain growth, and strengthening effect, which are contributed by the formation of Ti(C, N) with different compositions, sizes, and distributions. Due to the excellent corrosion resistance, formability, and mechanical properties, Ti-bearing stainless steel is widely applied to daily life and priority industries, including petroleum, aerospace, nuclear power, and transportation. However, complex inclusions can be formed after Ti addition in the metallurgy process. Moreover, those inclusions have adverse effects on the metallurgy and the quality of stainless steel, including the clogging of the submerged entry nozzle, layered defects, and surface defects. Therefore, it is important to develop the metallurgy of Ti-stabilized stainless steel. This paper discussed and concluded the investigation development of Ti-bearing stainless steel regarding the fundamentals of metallurgy, the formation and control of oxides and TiN, heterogeneous nucleation, and the influence of Ti on the mechanical properties of stainless steel. First, oxides with high melting points, including Al2O3, spinel, and (MgO?Al2O3)rich?CaO?TiOx, generally cause the clogging of the submerged entry nozzle in the Ti-bearing stainless steel. The optimized addition of Al, Ca, and Ti, as well as the control of slag, can decrease the amount of oxides with a high melting point. Second, the formation and growth of TiN and complex TiN inclusions happen during the cooling and the solidification of the titanium-stabilized stainless steel, which can collide and aggregate to form TiN clusters. Moreover, macro-oxides can promote the formation of TiN clusters. However, TiN or complex TiN inclusions can also work as heterogeneous nuclei for δ-Fe during the solidification of stainless steel and promote the generation of an equiaxed fine-grain structure. In addition to forming compounds, titanium can present as a solid solution state in steel and promote the formation of ferrite in austenitic stainless steel or increase the ferrite fraction in duplex stainless steel with its strong ferrite forming ability, which is beneficial to the improvement of the mechanical properties of stainless steel casting.
Abstract: Alloying is one of the main ways to achieve desirable properties in materials. The design concept is based on one or two metal elements, supplemented with multiple trace elements to achieve altered or optimized properties. With the advancement in technology, the traditional alloy has evolved from simple to complex compositions, thus improving their properties and promoting the progress of civilization. High-entropy alloys (HEAs) are a new type of multi-master alloys that are popular in the recent two decades. Unlike conventional alloys, HEAs comprise multiple alloying elements according to the isoatomic or non-isoatomic ratios and have several unique properties, such as high strength and hardness, excellent wear and corrosion resistance, thermal stability, and irradiation resistance. Refractory high-entropy alloys (RHEAs), HEAs made of refractory metals, have attracted great attention because of their excellent high-temperature mechanical properties. This paper discusses RHEAs from three aspects: processing methods, microstructure, and properties. Finally, this work presents the development and future prospects of RHEAs. RHEAs represented by MoNbTaVW alloys show better compressive yield strengths at high temperatures and a slower change of yield strength with temperature than traditional Ni-based high-temperature alloys. Compared with commercial superalloys, refractory metals, refractory alloys, and tool steels, RHEAs, such as MoNbTaVW, MoNbTaTiZr, and HfNbTiZr, show excellent wear resistance. RHEAs represented by W38Ta36Cr15V11 have no dislocation ring defect structure and excellent anti-irradiation performance after irradiation, except for the precipitation of small particles in the second phase. In this paper, two directions of future development of RHEAs were proposed: (1) establishing high-throughput experimental and computational methods to continue exploring composition and structural models of RHEAs and (2) exploring the service behavior of RHEAs in a multi-field coupled environment.
Abstract: With rapid social and economic development, high-efficiency welding technology has become an important development direction in the field of welding. In recent years, scholars and professionals in many countries have devoted themselves to further increasing the welding efficiency by improving welding materials, welding process, and arc-welding equipment. The welding efficiency can be increased using two approaches: one is increasing the welding speed, the other is increasing the welding deposition rate. Considering these two methods, typical technologies such as multiwire submerged arc welding (SAW) and multiwire gas metal arc welding (GMAW) were proposed. A twin-arc integrated cold wire hybrid welding system was established. The mechanical effect of the cold wire position on the welding process was studied, including its effects on heating, melting, and weld surface formation. Results show that the melting of cold wire depends on the front end of the weld pool, and the melting effect of the weld pool on the cold wire is not sufficient when the cold wire is fed in front of two leading wires. The end of the cold wire makes contact with the bottom surface of the weld pool with the continuous feeding of the cold wire. Droplets melted at the wire ends are ejected and fall on the base metal surface to generate a globular spatter with the backward motion of the base metal. The thermal distribution on the side of the weld pool decreases as the cold wire is fed inside of the two leading wires. Hence, the flow of molten metal is affected, ultimately leading to an uneven weld formation. The cold wire is stably inserted into the weld pool when fed behind the two leading wires, representing the optimum cold wire position. Moreover, the deposition rates increase with an increase in the cold wire feed speed and show little change under two-pulse phase differences (in-phase and reverse-phase pulse differences). The effect of arc heating and melting on the cold wire was most intense at the in-phase pulse current, followed by the reverse-phase pulse current and subsequently direct current.
Abstract: Deep learning is gaining attention in the field of mechanical equipment fault diagnosis. With the help of deep learning techniques, deep neural networks (DNNs) have great potential for machinery fault diagnosis. Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers to deliver state-of-the-art accuracy in various classifications of mechanical rotating parts. Convolutional neural networks (CNNs) are able to automatically learn multiple levels of representations from raw input datawithout introducing hand-coded rules or domain knowledge. Because of this powerful representation learning ability, deep learning has achieved great success in many fields. Although deep learning has achieved promising results in the field of machinery fault diagnosis, existing neural networks suffer from many limitations. The heavy and complex calculation amount puts forward strict requirements for computer hardware, which severely limits its application in actual engineering. To address this issue, this paper proposed a novel lightweight neural network model, ShuffleNet, for high-speed train wheelset bearing fault diagnosis. Based on the thought of module design, this model comprised several ShuffleNet units. Group convolution (GC) and deep separable convolution were used to improve the operation efficiency of traditional convolution in the ShuffleNet unit. Meanwhile, channel shuffle (CS) technology was adopted to overcome the grouping constraint caused by GC and improved the loss accuracy ofthenetwork model. CS operation makes it possible to build more powerful structures with multiple GC layers. Experimental results show that the proposed network model canbe applied in wheelset bearing fault diagnosis underacomplex working condition. Compared to the traditional CNN, ResNets, and Xception, the proposed method can greatly reducethecomputation cost while maintaining diagnosis accuracy. It is clear that the proposed lightweight neural network model, ShuffleNet, is superior to the above comparison models. This provides a new way forengineering applications of DNN technology and overcoming the limitations of computer hardware.
Abstract: Buffer zones in a production company are set before and after each processing equipment based on various factors such as workshop space in the hybrid-flow workshop, transportation capacity of the carrying equipment, ease of handling of the machine, machine productivity at various stages, and production cycle time. The objective of this paper was to optimizing the multi-objective scheduling problem in hybrid flow shop with limited buffer. As there was limited space (capacity) at front and rear buffers of each machine, transportation of workpieces in batches, limited carrying capacity of carrier equipment, differences in workability between parallel machines, and process determination, etc., were considered as resource limiting factors, and based upon these factors two-objective scheduling model was established with the goal of minimizing completion time and minimizing material transportation time. The two-objective scheduling model was added with minimization parallel machine front buffer space occupancy rate equilibrium index as a new goal, and established a three-objective scheduling model. In this article, NSGA-II and NSGA-III algorithms were used to solve the three-objective scheduling model, and the crossover and mutation parts of the algorithm were redesigned according to the model established. The actual production data of a marine pipe production enterprise was taken as an example and optimization results were compared with the actual production data. Thus the effectiveness of the algorithm was verified, and the difference between the two algorithms when processing the three-target scheduling model was compared, and it is concluded that NSGA-III has better convergence effect when processing the three-objective model. To explore the impact of different buffer volumes on production, target values ??under different buffer volumes were compared, and finally optimal buffer volume for each target was found out; then the two-objective model and the three-objective model were compared under different buffer volumes. The optimization results of these indicators prove the practical importance of adding the minimization of the parallel machine front buffer space occupancy rate balance index.
Abstract: There are two challenges with the traditional encoder–decoder framework. First, the encoder needs to compress all the necessary information of a source sentence into a fixed-length vector. Second, it is unable to model the alignment between the source and the target sentences, which is an essential aspect of structured output tasks, such as machine translation. To address these issues, the attention mechanism is introduced to the encoder–decoder model. This mechanism allows the model to align and translate by jointly learning a neural machine translation task. The whose core idea of this mechanism is to induce attention weights over the source sentences to prioritize the set of positions where relevant information is present for generating the next output token. Nowadays, this mechanism has become essential in neural networks, which have been researched for diverse applications. The present survey provides a systematic and comprehensive overview of the developments in attention modeling. The intuition behind attention modeling can be best explained by the simulation mechanism of human visual selectivity, which aims to select more relevant and critical information from tedious information for the current target task while ignoring other irrelevant information in a manner that assists in developing perception. In addition, attention mechanism is an efficient information selection and widely used in deep learning fields in recent years and played a pivotal role in natural language processing, speech recognition, and computer vision. This survey first briefly introduces the origin of the attention mechanism and defines a standard parametric and uniform model for encoder–decoder neural machine translation. Next, various techniques are grouped into coherent categories using types of alignment scores and number of sequences, abstraction levels, positions, and representations. A visual explanation of attention mechanism is then provided to a certain extent, and roles of attention mechanism in multiple application areas is summarized. Finally, this survey identified the future direction and challenges of the attention mechanism.
Abstract: To improve the performance of Wi-Fi fingerprint indoor positioning technology, a method based on convolutional neural networks (CNNs) for channel state information (CSI) fingerprint indoor positioning is proposed. This method fully exploits the feature extraction capabilities of CNNs, applies the combination of amplitude difference and phase difference information as training data in the offline phase, and uses the trained CNN network model for an online test. In the online phase, for different experimental scenarios, by analyzing the variance of the amplitude information and phase information, the amplitude difference and phase difference information of the test data are weighted to obtain a certain universal weight factor for a better positioning result. At the same time, considering the characteristics of terminal mobility during real-time positioning, the CSI information sampled twice in succession is adopted as test data to increase the diversity of test data. To address the disadvantage of poor positioning performance of traditional probability-based positioning algorithms, an improved probability-based fingerprint matching algorithm is introduced. By passing the CSI information of the point to be located through the CNN network model, it can output the probability average value corresponding to the reference position with the highest probability in all test data packets and weight it with the reference position coordinate to estimate the point to be located. In addition, to enhance the universality of the algorithm, a dual-node positioning scheme is proposed for complex indoor scenes to improve positioning accuracy. Experiments are conducted in two positioning scenarios in a corridor and laboratory, including the amplitude difference positioning performance, the average positioning error of each positioning method, and the performance comparison of positioning algorithms. The information joint positioning algorithm obtains an average positioning error of 24.7 and 48.1 cm, which verifies the effectiveness of the proposed algorithm.
Abstract: Modernization of urban infrastructure is the premise for improving urban operation efficiency. The traditional direct burying method of the municipal public pipeline requires repeated excavation for maintenance, which seriously affects the traffic and appearance of the city and interferes with the everyday life and work order of residents. With the rapid development of urbanization recently, the city’s underground utility tunnel appears at a historical juncture. To cope with the industry’s urgent need for efficient and green construction technology, China is strongly promoting urban utility tunnels and its development toward prefabrication. The prefabricated utility tunnel efficiently uses the urban underground space, intensively manages various municipal pipelines, and solves the “zipper road” problem; it also has the advantages of increased production efficiency in a short construction period and green environmental protection. The joint is the weakest link of the structure in a prefabricated utility tunnel, and its mechanical properties directly affect the deformation and bearing capacity of the entire structure. A new type of prefabricated double cabin utility tunnel with a “U-shaped ferrule joint bars connection” was proposed. The validity of the method was confirmed through testing the mechanical properties of four full-scale joints, including one bottom L-shaped cast-in-place side joint, one bottom L-shaped assembly side joint, one top L-shaped assembly joint, and one bottom T-shaped assembly joint specimen. The result obtained the mechanical properties of the joint full-scale specimen, such as cracking load, crack development law, bearing capacity, failure mode, and member ductility. Furthermore, the specimens of new prefabricated utility tunnel joints had flexure-shear failures near the corner points despite their high bearing capacity and ductility. Using U-shaped ferrule joint bars provides consistent performance and can obtain mechanical properties comparable with those of cast-in-place joint specimens.
Abstract: The microporous adsorbent ZSM-5 has been extensively applied for toluene adsorption. In this work, ZSM-5 was modified with alkali metals Li, Na, and K for toluene adsorption. The effects of the alkali metals introduced into ZSM-5 on the ZSM-5 microporous structure and toluene adsorption were studied via characterization techniques and mathematical modeling. Moreover, the influence of alkali metals on toluene adsorption was investigated from four aspects: adsorption capacity, exothermic energy, diffusion resistance, and desorption activation energy. The experimental results show that the introduction of alkali metal affect the ZSM-5 microporous structure in different aspects. The pore size, specific surface area, and pore volume of the modified ZSM-5 were of the following order: Li?ZSM-5 > Na?ZSM-5 > K?ZSM-5, corresponding to increasing ionic radius of the metals (Li+ < Na+ < K+). Likewise, the static saturated adsorption capacity was of the order: Li?ZSM-5 (0.363 mmol·g?1) > Na?ZSM-5 (0.360 mmol·g?1）> K?ZSM-5 (0.325 mmol·g?1). The constant concentration wave model could well fit the adsorption and diffusion behaviors of toluene onto ZSM-5. The steric hindrance and electrostatic binding force played a dominant role in toluene diffusion in the ZSM-5 channel at high and low inlet gas concentrations, respectively. At a higher inlet concentration (155 mg·m?3), the influence of alkali metal modification on the internal diffusion resistance for the three adsorbents was of the order: Li?ZSM-5< Na?ZSM-5 < K?ZSM-5, whereas at a lower inlet concentration (25 mg·m?3), the trend was Li?ZSM-5 > Na?ZSM-5 > K?ZSM-5. The desorption kinetics analysis show that Na?ZSM-5 exhibite a better regeneration potential, due to its large pore size and moderate adsorption strength. In this study, the mechanism of alkali-metal modification of the adsorption behavior toward toluene was systematically investigated from two aspects: steric hindrance and adsorption strength to provide a certain reference for selecting a suitable adsorbent in complex practical environments.
Abstract: The main sources of fine particulate matter in the air are automobile exhaust and dust-containing hot flue gas emitted from combustion in the process of industrial manufacturing and municipal solid waste incineration, both of which are hard to clean at high temperatures. Ceramic membranes maintain high strength at high temperatures and an acid or alkaline atmosphere, and have a micron-scale and tortuous pores that block dust particles. The ceramic membrane is one of the most effective materials for successful hot flue gas cleaning as used in the integrated gasification combined cycle. Its filtration and regeneration performance are related to the deposition and desorption mechanism of dust particles in the channel of the membrane. In this study, a physical model of ceramic membranes of various porosities was established. Boundary and deposition conditions were then set up by combining continuity, momentum, and energy equations to simulate the flow of hot flue gas and the deposition and desorption process of dust particles during ceramic membrane filtration and pulse back-blowing. The results show that when the filtration velocity is low and porosity of the ceramic membrane is high, it is easy for dust particles to deposit in the membrane channel. Increasing back-blowing pressure prolongs back-blowing time during pulse back-blowing so that dust particles easily desorb from the channel of the ceramic membrane. When a ceramic membrane tube with a thickness of 20 mm, a length of 1.5 m, and a porosity of 40% is used to filtrate flue gas with a filtration temperature of 1000 °C, a flow rate of 1 m·min?1, and a pressure of 0.1 MPa, the blowback pressure should not be <0.3 MPa, blowback time should be longer than 0.02 s, and pulse blowback time interval should be more than 452 s.
Abstract: Petroleum exploitation plays a very important role in national energy security. With continuous exploitation of oil fields in my country, the efficiency of conventional water injection oil production is decreasing year by year. Enhanced oil recovery (EOR) technologies, such as polymer flooding, microbial flooding, micro–nano flooding, and other flooding technologies have been proposed and developed for application. However, the microscopic displacement mechanism and displacement effect of these technologies are still unclear. Current oil displacement research needs to be verified by core displacement experiments. However, the current displacement experiments all use artificial cores, glass etching channels, photoetched microchannels, etc., as the oil displacement environment. These displacement environments are insufficient in terms of oil displacement dimensions and observation phenomena. Due to this, there is an urgent need for a core manufacturing method that is more suitable for laboratory oil displacement research. In this study, we proposed a method for manufacturing a simulated three-dimensional core structure based on micro-stereolithography technology. This method not only has the advantages of fast manufacturing speed and high forming accuracy, but is also able to realize the visualization, parameterization, and customized design of a micron structure. The core model self-searched by stereo lithography has a three-dimensional pore structure in the order of hundreds of microns and can be used to simulate the experimental study of reservoir displacement flow mechanism. In this research, a high-precision surface projection micro-stereolithography equipment was built, and the optimal printing process parameters were obtained through a combination of theoretical analysis and experiments. Then, a microsphere stacked core model was proposed that can be used to simulate formation cores. By analyzing the forming mechanism of the core model, a stacking method was selected with a higher forming accuracy to design the core model. Finally, the core of a 100-micron-sized microsphere accumulation was realized by micro-stereolithography to achieve three-dimensional molding. The simulated core manufacturing method in this study has high adaptability to special core structure manufacturing and provides a new idea for studying the microscopic displacement mechanism of various EOR technologies under a laboratory microscope.
Abstract: Since the 1950s, international studies have confirmed the technical advantages of high-voltage direct current (HVDC) transmission projects, such as large capacity, low loss, and high stability. In recent years, due to the reverse distribution of energy demand and resources in China, large-scale long-distance transportation of energy is inevitable. HVDC is especially suitable for large-scale transmission projects such as “west to east power transmission” and “north to south power transmission.” Therefore, a number of HVDC projects have been built in China since the 1980s. However, with the large-scale construction of HVDC transmission projects, the interference effect of HVDC grounding electrode on metal facilities is increasingly prominent, in which the buried pipeline will produce high amplitude of pipe-to-soil potential under HVDC interference. As a result, HVDC interference can cause damage to pipelines, personnel, and related equipment. However, there is no systematic analysis of the causes of high amplitude of pipe-to-soil potential at home and at abroad. Based on the actual engineering parameters, this paper established a calculation model of the high-voltage direct current interference electric field on the buried pipeline and a numerical simulation technology was used to explore the causes of the high amplitude of pipe-to-soil potential under HVDC interference. Moreover, the influence of the distance between the grounding electrode and the pipeline, the type of anti-corrosion coating, the length of the pipeline, and the soil structure on the pipe ground potential under HVDC interference was investigated. Results reveal that the high amplitude of pipe-to-soil potential under HVDC interference is under the joint action of the short distance between the grounding electrode and the pipeline, the high insulation performance of the anti-corrosion layer, the large length of the pipeline, and the soil layered structure with low resistivity at upper and high resistivity at lower.
Abstract: An energy pile is a new type of ground source heat pump system. A heat exchanger is casted into the concrete pile foundation of a building structure for the purpose of heating or cooling the building through heat exchange between the pile foundation and surrounding soil. An energy pile can be developed rapidly because of its high heat transfer efficiency and stable structure and because it requires no additional drilling requirements. In the long-term operation, energy piles have to bear both the overlying and thermal loads caused by changes in the temperature field. Thus, accurately evaluating the temperature field of an energy pile and its surrounding soil is one of the key problems in the design and application of energy piles. To improve the heat transfer efficiency of energy piles, U-type, W-type, spiral type, and similar types of coils have been developed to be casted into the energy pile. Results of thermal efficiency analysis show that the spiral type coil has the best heating and cooling performance and was nearly 150% more thermally efficient than the double U-type coil. Thus, a spiral coil is selected as the main coils’ form in the current practical application. However, due to the complex heat exchange structure of the spiral pipe, the present analytical model had to be simplified to accurately characterize the temperature field characteristics of a spiral pipe casted in an energy pile. In this paper, the spiral pipe was regarded as a three-dimensional spiral heat source. Considering the existing heat transfer model, an analytical solution of the temperature field was obtained by integrating green’s function and the first curve function; then, the high-precision, three-dimensional (3-D) heat transfer model of the spiral pipe was established considering the time, space, buried pipe parameters, and thermal property of host soil. In addition, a 3-D model of a spiral pipe casted in an energy pile was created in the numerical simulation software COMSOL; after simulation, the numerical solution of the temperature field was obtained. The contrastive results showed that the built 3-D spiral heat source model has high analytical accuracy. Finally, based on the analytical model, the spatial distribution and time effect of a spiral pipe casted in an energy pile were discussed.
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
