Abstract: With the rapid economic development in China, more areas of industrial contaminated soil has been left unused because of industrial relocation or environmental protection. Considering the chromium (salt) industrial wasteland, the area of chromium-contaminated soil caused by the accumulation of chromium slag has reached 5 million square meters, and its direct utilization can result in health hazards to the public and threaten the environment. Therefore, it is of great practical significance to carry out research on economic, efficient, and clean methods for chromium-contaminated soil remediation. In this paper, the origin and occurrence of the chromium in soil, their extraction methods, and the research progress of chromium-contaminated soil in and outside China were reviewed. First, the occurrence of the chromium in soil was discussed. It is found that Cr exists predominantly in Cr(Ⅲ) and Cr(Ⅵ) oxidation states, whereby Cr(Ⅲ) is the more stable; under most prevailing environmental conditions Cr(Ⅵ) is rapidly reduced to Cr(Ⅲ). The methods of extracting chromium from soil were presented, including Tessier sequential extraction procedure and the European Community Bureau of Reference(BCR) three-step sequential extraction procedure, and then the two continuous extraction methods were compared and evaluated. Afterward, the remediation techniques of chromium-contaminated soil were systematically reviewed, including engineering physical repair methods, dilution methods, immobilization and stabilization, chemical reduction, electrokinetics repair, and bioremediation. The advantages and disadvantages of the various remediation techniques were compared, summarized, and evaluated. The developments of chromium-contaminated soil remediation technologies in the future were also explored, including the clean remediation technologies, combination of several remediation technologies, and novel nano-remediation materials. Accordingly, suggestions for the remediation of different chromium-contaminated soils were presented, which can provide references for clean and efficient remediation of chromium-contaminated soils.
Abstract: This paper reviewed the recent development of primary carbides in H13 steel from the aspects of solidification segregation theory, solidification method, production process, and alloy design. The relationship between the production process of H13 steel and the characteristics of primary carbides was clarified. During the solidification of H13 steel, primary carbides can be easily generated by dendritic segregation. The primary carbides in H13 steel can be divided into polygonal, stripy, blocky, and eutectic structures according to the different shapes and can be divided into MC, M2C, M7C3, and M23C6 according to the different structures. The primary carbides can also be classified as Mo-rich, V-rich, and Ti/Nb-rich carbides according to the different compositions. Primary carbides are detrimental to the performance of H13 steel because cracks can easily form around primary carbides during service of the materials. The widely used methods of controlling the primary carbides in H13 steel under industrial production conditions, including solidification control, modification treatment, high-temperature diffusion of the ingot, and alloy composition optimization, were introduced. Modification treatment and solidification control are able to control the size and quantity of primary carbides but are unable to avoid the precipitation of primary carbides entirely. The stability of primary carbides can be relieved by composition optimization. High-temperature homogenization treatment of ingot is the most important means of controlling primary carbides in H13 steel. However, the heating temperature and holding time need further investigation.
Abstract: Rare-earth metals play a very important role in the development of high-tech industries and the research of functional materials. The demand for high-purity rare-earth metals has rapidly increased because of the development of modern society and the rare-earth industry. However, the purity of commercial rare-earth metal materials is the key factor limiting the rapid development of rare-earth industry. The major impurities in commercial rare-earth metal materials are gas impurities, especially oxygen. The removal of oxygen impurities is extremely challenging because of their strong affinity, which causes the problem of high oxygen concentrations of raw rare-earth metal materials. Therefore, effectively removing oxygen purities is the key to achieve ultra-high purity rare-earth metals. In recent years, several new and innovative strategies to remove oxygen impurities from rare earth metals have been proposed and investigated. To overcome the kinetic and thermodynamic barriers, various driving forces have been creatively introduced into the refining process. This article presented some novel purification methods to remove oxygen impurities, including active metal external getting method, hydrogen plasma arc melting method and hydrogen in-situ refining method. Experimental results show that the oxygen concentrations in rare-earth metals can be reduced effectively by introducing various driving forces. The optimum process conditions of these techniques were introduced in detail, with the final concentrations of oxygen being reduced to below 5×10-5. The design concept and refining mechanism of the driving forces, including active metal, hydrogen plasma and dissolved active hydrogen atoms in rare-earth metal, were discussed systematically in this paper. The refining principle and migration mechanism of oxygen impurities were also discussed by combined experimental and calculated studies. The FAST-2D combined Stefan simulating method, 18O2 isotope tracking method and CALPHAD method were used to study the purification mechanism. The study results provide theoretical basis for the removal of oxygen impurities in rare-earth metals. The methods demonstrated here may provide insight on the future research in rare-earth purification.
Abstract: Coal and gas outburst seriously threatens the safety of underground coal mining. With the increase in coal mining depth, the geological conditions of coal mines become complicated, which adversely affects the safety of coal mining production. Prominent prediction is an important link to reduce the damage caused by outburst accidents. This study investigated the prediction model of coal and gas outburst. On the basis of the analysis of the gas geological factors of coal and gas outburst, a prediction system including 3 major indices (i.e., gas, coal, and crustal stress indices) and 12 minor indices (e.g., gas pressure and tectonic coal thickness) was established. A multi-index coupling prediction model based on the improved input and output of the gray correlation model was proposed. Network analysis and multi-class distance discriminant method were also comprehensive applied to improve the accuracy of coal and gas outburst index prediction. On the basis of the comprehensive analysis of the gas geological factors of coal and gas outburst, the model calculates the weight of the prediction index, classifies the possible grade of the outburst, and derives the discriminant formulas to discriminate the possibility of outbursts. Taking the Pingdingshan No. 8 coal mine as an example, the model estimated the probability of coal and gas outburst in eight sets of prediction samples. The predicted results are consistent with the actual conditions, provide technical support for coal mine and gas outburst prevention, and prove the accuracy and applicability of the multi-index coupling prediction model.
Abstract: The reduction behaviors of sinter and lump ores, which account for 90% of the raw materials charged into blast furnace process, are important to coke reduction in the ironmaking industry. The isothermal reduction behaviors of sinter and lump ores have been extensively studied; however, non-isothermal conditions, which are more consistent with the temperature change characteristics in a blast furnace, have been rarely investigated in terms of their reduction processes. Studies on the reduction behaviors of calcium ferrite and hematite, which are individually contained in sinter and lump ores, can provide more significant guidance to the practical operation. Comparisons of the reduction behaviors of calcium ferrite and hematite involves thermodynamic parameters such as the starting reduction temperature and kinetic parameters such as activation energy and model function. Considering reduction processes, hematite has been clearly explored by numerous works to an extent far more than calcium ferrite. In addition, in studying the reduction behaviors of calcium ferrite and hematite, pellet samples of 1-100 mm were the focus in the past and rarely micron-sized powder samples (1-100 μm). However, nowadays, micron-sized particles are extensively applied on iron ores reduction in fluidized bed process and non-blast furnace process, such as FINEX® method; therefore, in this study, calcium ferrite and hematite were compared, considering their reduction routes and reduction kinetics. Non-isothermal reduction experiments of powdery calcium ferrite and hematite heated up to 1123 K with a rate of 10 K·min-1 in a continuous stream of 30% CO and 70% N2 were conducted through thermo-gravimetric analysis. The results show that the reduction processes of calcium ferrite and hematite begin at 873 K and 623 K, respectively. Reduction rate analysis and subsequent X-Ray diffraction measurements at various stages reveal that the reduction of calcium ferrite can be divided into two steps:CaO·Fe2O3 → 2CaO·Fe2O3 → Fe, whereas that of hematite mainly comprises three steps:Fe2O3 → Fe3O4 →FeO → Fe. The activation energy was calculated by Freeman-Carroll method, and the average values of calcium ferrite and hematite reduction are 49.88 and 43.74 kJ·mol-1, respectively. The reduction of calcium ferrite can be described by random instant nucleation and two-dimensional growth of nuclei model; its corresponding model function is Avrami-Erofeev equation with an integral form of[-ln(1-α)]n, whereas the reduction of hematite was initially expressed by a tertiary chemical reaction model (reduction degree α=0.1~0.5) with an integral form of 1-(1-α)3, and subsequently by a two-dimensional cylindrical diffusion model (α=0.5~0.9) with an integral form of α+(1-α) ln(1-α).
Abstract: Blast furnace volatilizing (smelting) and reverberatory furnace process is the main reduction method in the current antimony smelting process, and it is associated with problems such as a long production flow, high energy consumption, and SO2 flue gas pollution. Thus, in this paper, a new process, based on the combination of beneficiation and metallurgy, was proposed for the direct extraction of antimony from stibnite concentrate. Using ZnO and carbon as a sulfur-fixing agent and reductant, respectively, antimony sulfide was transformed to Sb and ZnS metals, and then the mixture was separated by a mineral separation method. The effects of calcination temperature, carbon particle size, ZnO dosage, and calcination time on the conversion rate of Sb and sulfur-fixing rate of ZnO were investigated in detail by controlled variables method. The optimal conditions are as follows:calcination temperature 800℃, carbon particle size 100~150 mesh, ZnO dosage 1.0 times the theoretical amount, and roasting time 2 h. Under these conditions, the antimony generation rate and sulfur-fixing rate of ZnO are 90.4% and 94.8%, respectively. The antimony generation rate and sulfur-fixing rate of ZnO can be improved by increasing the reaction temperature and ZnO dosage. Meanwhile, the phase analysis results of the reaction products and thermodynamic calculations of reactions indicate that the reaction paths of Sb2S3 and ZnO comprise two steps:First, Sb2S3 reacts with ZnO to generate Sb2O3, and then after 700℃, it is reduced to a large amount of antimony. In the comprehensive experiments of different grades of antimony, about 90% of antimony generation rate and 88% of sulfur-fixing rate are realized, which demonstrates the feasibility of the new process. The new process is characterized by low temperature and low carbon usage, and it is clean and environment friendly; thus, it is suitable for industrial production.
Abstract: The solidification behavior and microstructures evolution of cast Ni-based superalloy K424 under different cooling rates were investigated by isothermal solidification quenching experiments and differential scanning calorimetry (DSC). The microstructures and segregation characteristics of K424 were analyzed at different isothermal temperatures and cooling rates using optical microscopy, scanning electron microscopy, and energy-dispersive spectrometry (EDS). The isothermal solidification, microstructure, and distribution characteristics of elements at the final solidification stage were also investigated, and the liquidus, solidus, and the formation temperatures of the main phases were evaluated. Furthermore, the influence of cooling rate on the morphology and size of MC carbides, (γ +γ') eutectic, and precipitated γ' phase were discussed. The results show that the solidification of the K424 alloy follows the sequence:(1) L → L + γ at 1345℃:the solidification begins with the formation of primary γ, and the liquidus temperature is 1345℃; (2) L → L + γ + MC at 1308℃:as the solidification continues, Ti and Nb are enriched in the liquid interdendrite, which results in the formation of MC carbides at 1308℃; (3) L → γ + (γ + γ') at 1260℃:the precipitation of the (γ + γ') eutectic occurs at about 1260℃ because of non-equilibrium solidification. Finally, the solidification ends with a solidus temperature of 1237℃. Furthermore, it is found that the precipitation of (γ + γ') eutectic at the interdendtitic regions is closely related to the cooling rate and the severe segregation behavior of Al and Ti into the residual liquid at the final solidification stage. With the increase of cooling rate, the quantity and size of MC carbides and eutectic first increase and then decrease. Moreover, with increasing cooling rate, γ' shapes transform from irregular petal-like structure to near cuboidal and spherical patterns, and the size scale of γ' precipitates decreases from 2 μm to 60 nm.
Abstract: In the case of preheating and non-preheating, the rapid prototyping system of high-power fiber laser and electromagnetic induction heating equipment was used to fabricate 12CrNi2 alloy steel. The microstructure of the molded parts was observed under a scanning electron microscope, and the hardness test of different parts was conducted using the Victorinox hardness tester. The tensile properties in different directions were tested using the universal material testing machine. This study investigated the effect of preheating on the microstructure, hardness, and tensile properties of laser melting deposited 12CrNi2 alloy steel in different directions. The obtained results show that the microstructure of the single-channel molten pool without preheating is lath martensite, and the molten pool of block-shaped forming parts is tempered martensite and bainite mixed structure. No obvious structural difference between XOZ and YOZ sections is observed. However, the overall hardness of the YOZ cross section is larger than that of the XOZ cross section. Large-scale macroscopic crack defects appear in both sections, and the mechanical properties are poor. Under preheating conditions, bainite transformation occurs in the molten pool because of the decrease in the temperature gradient. The single-channel molten pool shows an excellent bainite structure. No tempered martensite transformation in the molten pool of block-shaped forming parts, mainly granular bainite, is observed. Cross-sectional hardness distribution is more uniform with preheating than without preheating. High tensile strength and low plasticity are detected in the tensile and overlap directions. The tensile strength is up to 1189 MPa, the yield strength is 951 MPa, and the elongation is only 2.8%. No obvious anisotropy in performance is observed. Preheating can reduce the temperature gradient in the molten pool, reduce the thermal stress, effectively control the crack defects, promote the homogenization of the microstructure, reduce the anisotropy of the microstructure and properties, and improve the mechanical properties of the alloy steel forming parts.
Abstract: Although Fe-Ni wires have numerous potential applications, the effect of heat treatments on the microstructures and properties of Fe-Ni wires is currently unclear. In this study, different high-temperature annealing and low-temperature aging treatments (i.e., ① annealing at 950℃ for 3 h+quenching, ② annealing at 950℃ for 3 h+quenching+aging at 500℃ for 2 h, and ③ aging at 500℃ for 2 h) were applied to cold-drawn Fe-36.24% Ni alloy wires to comparatively investigate their influences on the microstructural evolution, tensile strength, and thermal expansion coefficient, with the aid of microstructural characterization methods, such as X-ray diffraction, optical microscopy, atomic force microscopy, and transmission electron microscopy, as well as property measurements, such as room-temperature tensile testing and thermal expansion coefficient. The experimental results clearly show that the as-drawn Fe-Ni wire, although having a high tensile strength, exhibits an unfavorable high thermal expansion coefficient. The Fe-Ni wires annealed at 950℃ (wires subjected to ① and ②) have a relatively low thermal expansion coefficient but exhibit insufficient strength. In comparison, the wire aged at 500℃ (wire subjected to ③) shows a high strength (1189 MPa) and a low thermal expansion coefficient (0.2×10-6℃-1) at the same time. The relative strengthening mechanisms and factors affecting the thermal expansion coefficient are discussed and analyzed in terms of the microstructures. Grain boundary strengthening and dislocation hardening are observed to be the dominant strengthening mechanisms of the Fe-Ni wires, and the solute atom-dislocation interaction is mainly responsible for the evolution of the thermal expansion coefficient. The present work clearly demonstrates that suitable heat treatments are important for the optimization of the strength/thermal expansion coefficient of Fe-Ni alloy wires, which will be helpful for material design and technology tailoring of Fe-Ni wires to develop a new alloy with enhanced performance.
Abstract: Copper-clad aluminum wires are extensively applied in aerospace, telecommunications, national defense industry, and other fields, because of the combined advantages of the excellent conductivity, thermal conductivity, and low contact resistance of copper and the low density, corrosion resistance, and low costs of aluminum. In this study, a composite wire with high interfacial bonding quality was obtained by hot rotary swaging, which can be utilized in manufacturing to achieve high efficiency and high quality because of its feature of the large single-pass deformation. The processed wire was then prepared by drawing into micro-wires, and given this, a simple, inexpensive, and highly efficient method for preparing micro-wires was developed in this study. Copper-clad aluminum wires with a diameter of φ65 μm, uniformly thick coating, glossy surface, and good interfacial bonding were prepared by the hot rotary swaging-drawing method. The rotary swaging parameters and the microstructure and interfacial bonding of the composite wire were studied, and the effects of drawing and intermediate annealing on its microstructure and properties were discussed. The results show that the reasonable swaging parameters are 350℃ swaging temperature with 40% single-pass deformation. After the rotary swaging, dynamic recrystallization microstructures and interface diffusion layer with thickness of 0.7 μm are formed. The optimum annealing parameter is 350℃/30 min (350℃ annealing temperature with 30 min annealing time), under which the elongation reaches 35.7%, the thickness of interface diffusion layer is 2.1 μm, and the copper layer and the aluminum core are recrystallized with the formation of equiaxed grains. When the annealing temperature exceeds 350℃, copper and aluminum grains and the interface layer thickness increase, which will lead to a lower wire elongation. A wire of φ0.96 mm is fabricated by a 15%-20% single-pass deformation, and then the φ65 μm diameter wire is manufactured by an 8%-15% single-pass deformation without annealing. In the drawing process, 〈111〉 silk texture appears in the copper layer and the aluminum core.
Abstract: Numerical simulation technology is widely used in material forming process optimization and mold design. Although large volumes of simulation result data can be obtained, it is difficult to directly derive the relationship between the forming quality and the forming process parameters. To extract the potential knowledge latent in the simulation results, a systematic, robust, and efficient knowledge discovery technology is necessary, such as artificial intelligence technology, which has become one of the important research directions of material forming and processing. In this study the deep drawing process of a motorcycle fuel tank cover was taken as an example. A motorcycle fuel tank has complicated surfaces and local small fillets, and during its formation, the side wall and fillet are likely to wrinkle and rupture, respectively, because of local deep and uneven deformation. It is important to determine the forming parameters to produce high quality tank cover that satisfies the surface quality requirements. Compared with the iterative dichotomiser 3 (ID3) decision tree algorithm, the classification and regression decision tree (CART) algorithm is advantageous in terms of faster computation speed, higher stability, and supporting multiple segmentation of continuous data. Furthermore, compared with other algorithms such as support vector machines (SVM) and logistic regression (LR), using the CART decision tree algorithm, the decision tree diagram can be established, and knowledge rules can be visually extracted. Combining the artificial intelligence technology of CART decision tree and the model cross validation method of F1 score, Scikit-Learn, an open-source library of Python platform was used to carry out knowledge discovery from the numerical simulation results of the tank cover deep drawing process. The key forming process parameters of the tank cover, which are blank holder force, the height of the draw bead, and radius of the die fillet, were identified. The optimal eigenvalues and the optimal segmentation points of CART decision tree were selected according to the minimization criteria of Gini index, and the process rules were extracted from the CART decision tree of the forming quality index and the established process parameters. The tank cover drawing process example shows that the knowledge discovery technology based on CART decision tree theory is a feasible way to mine potential knowledge from the numerical simulation results of material forming process.
Abstract: A set of experimental devices for the measurement of indoor oxygen supply in an enclosed architectural space was built. The devices were used to analyze the effects of the number and diameter of oxygen-feeding ports, oxygen flow rate, and oxygen-feeding mode on the indoor oxygen enrichment characteristics and efficiency of an architectural space. Results show that the distribution of the maximum axial oxygen concentration tends to decline with axial distance under different numbers and diameters of oxygen-feeding ports, oxygen flow rates, and oxygen-feeding modes. Axial oxygen concentration rapidly decreases when the axial distance to the oxygen-feeding port ranges from 0 m to 0.55. In general, the oxygen-enriched region that forms in a single oxygen-feeding port under different pipe diameters and oxygen flow rates presents a flat elliptical shape. The oxygen-enriched area expands under a constant oxygen-feeding pipe diameter and an increasing oxygen flow rate. The oxygen-enriched area that forms in double oxygen-feeding ports, wherein one is positioned vertically forward and the other port is positioned 45° opposite the forward-facing port, has a bifurcated shape with one pointed head and one rounded head. The oxygen-enriched area that forms in the vertical forward-facing port is larger than that in the 45° opposing port. Under back-to-back oxygen feeding, the oxygen-enriched area that forms in double oxygen-feeding ports with the pipe diameter of 6 mm generally exhibits a two-bladed fan shape, whereas that in double oxygen-feeding ports with the pipe diameter of 10 mm appears as two overlapping semicircles. Under the total oxygen delivery flow rate of 1 m3·h-1, the range of oxygen feeding in double oxygen-feeding ports with the pipe diameter of 6 mm and 45° angle is the largest and that in double oxygen-feeding ports with the pipe diameter of 10 mm and vertical forward position is the smallest. Under a constant total oxygen flow rate and oxygen-feeding mode, the oxygen-enriched area that forms in the single oxygen-feeding port in the vertical forward position is 20% larger than that in the double oxygen-feeding ports in the vertical forward position. Under the same number of oxygen-feeding port, oxygen flow rate, and oxygen-feeding mode, the oxygen-enriched area in the oxygen-feeding port with the pipe diameter of 6 mm is approximately 60% larger than that in the oxygen-feeding port with the pipe diameter of 10 mm.
Abstract: The issues of model set construction and weighting algorithm analysis in multiple model adaptive control of discrete-time systems with large parameter uncertainty are considered in this paper. First, to improve system performance by reducing the calculation burden and relaxing the convergence conditions for the classical weighting algorithm, a new weighting algorithm is adopted, which is based on the model output errors of the multi-model adaptive control system with a self-tuning model. Second, the weighting algorithm convergence is analyzed in two cases:when the model set contains the true model of plant and it tends to the fixed model, and when the model set does not contain the true model of plant and it tends to the self-tuning model. Third, according to the virtual equivalent system (VES) concept and methodology, the stability of weighted multiple model adaptive control (WMMAC) with a self-tuning model is presented under a unified framework. The analysis procedures for linear time-invariant (LTI) and parameter jump plants are independent of specific local control methods and weighting algorithm, which only require that each local controller stabilizes the corresponding local model, the output of the formed closed-loop system tracks the reference signal, and the weighting algorithm is convergent. The principal contributions of the paper are the analysis of global stability and the convergence of the overall system with a self-tuning model. Compared with the stability results of WMMAC in the early stage, the constraint condition that the model set only has fixed models is relaxed, which can enlarge the application range of the stability results in theory. In addition, because of the introduction of a self-tuning controller, the control performance of the system is significantly improved when the real model of the plant is not included in the model set. Finally, computer simulation results verify the feasibility and effectiveness of the proposed method.
Abstract: Optimization problems of nonlinear constrained single objective system are common in engineering and many other fields. Considering practical applications, many optimization methods have been proposed to optimize such systems whose accurate mathematical models are easily constructed. However, as more variables are being considered in practical applications, objective systems are becoming more complex, so that corresponding accurate mathematical models are difficult to be constructed. Many previous scholars mainly used back propagation (BP) neural network and basic optimization algorithms to successfully solve systems that are without accurate mathematical models. But the optimization accuracy still needs to be further improved. In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. First, the SVM is used to construct the predicted model of nonlinear constrained single objective system. Then, the immune particle swarm algorithm, which incorporates the self-regulatory mechanism of the immune system, is used to optimize the system based on the predicted model. The proposed method is compared with a method based on a combination of BP neural network and particle swarm optimization algorithm (BP-PSO). The optimization effects of the two methods are studied under few training samples by reducing the number of training samples. The simulation results show that the SVM-IPSO has a higher optimization ability under the same sample size conditions, and when the number of samples decreases, the SVM-IPSO method can still obtain more stable and accurate system optimization values than the BP-PSO method. Hence, the SVM-IPSO method provides a new and better solution to this kind of problems.
Abstract: To improve the level of intelligent monitoring, maintenance, and management of transmission lines, research on inspection robots, and key technologies of overhead transmission line have attracted wide attention. With the breakthrough of the theory and technology of the internet of things, robot data transmission based on wireless sensor networks has become an active research area in the field of inspection robotics. Several researchers assume that robots are mobile nodes in wireless sensor networks, and the non-mobile communication node in the network is considered as a static node. The most crucial and difficult aspect of this research is coordinating the relationship among transmission success rate, transmission energy consumption, and delay of dynamic sensors networks. To address this difficulty, a novel method was proposed for the intelligent monitoring and communication system of power grids based on inspection robots. This method aims to realize the remote data collection of inspection robot by delay-tolerant mobile sensor networks for inspection robot (DTMSNR), which is featured by nodes heterogeneity, sparse sensor fields, random mobility, intermittent connectivity, and delay tolerance. It adopts the mobile robot position-based delivery (MPD) method to solve the inadaptability of the traditional methods of sensor networks. A path-constrained random motion model was established, in order to accurately calculate the network pose information of the inspection robot. The MPD adopts the relative position information of the robot and other nodes to compute transmission probability and selects the message transmission path. This method uses mechanisms of robot message priority transfer and failure time to manage the message queue, considering the different delay requirements for messages. Multiple simulation scenarios were performed, and the influences of different parameters with four routing algorithms were discussed. The results indicate that compared with the commonly used DTMSN data transmission methods, the proposed method can provide a higher delivery ratio and lower transport delay under appropriate transmission energy consumption.
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
