National Defense Construction Research Articles

A study on particle size of slag on properties of magnesium potassium phosphate cement

AbstractMagnesium potassium phosphate cement (MKPC) presents a broad application prospect in engineering fast repairing, reinforcement, hazardous material, and national defense construction, due to its good properties such as fast hardening and early strength, high bonding strength, and wide environmental adaptability. In this work, the effect of slag with different particle size on the workability, mechanical properties, and hydration products of MKPC was investigated. The results showed that the compositions of slag in the particle size range 75–300 µm are quite different. A decrease in the particle size of slag resulted in reduction of the fluidity of MKPC from 175 to 108 mm and shortening the setting time from 1300 to 850 s. The compressive strength of MKPC (curing for 3 h) does no change much as the particle size of slag varies, and slag with the particle size in the range of 115–300 µm slightly increase the 3‐h‐compressive strength of MKPC, since the compressive strength values are in the vicinity of 13 ± 2 MPa. As the curing age increases, physical effect and hydration activity of slag concurrently dominate the mechanical properties of MKPC, and when the hydration activity of the slag exceeds the adverse effect caused by fine particles, the compressive strength increases. Slag particle size can significantly improve the long‐term compressive strength of MKPC, which can effectively reduce the cost and can be used as a repair material with better durability.

The Relationship between the Construction of Community for the Chinese Nation and the Subjectivity of the People—Based on the Community Analysis

Throughout the course of the development of the Chinese nation, the people of different ethnic groups have formed common interests, beliefs, emotions, and culture in different historical periods, and have closely united in aspects such as national unity, economic development, technological progress, and national defense construction, forming a community for the Chinese nation. The subjectivity of the people is a key thread of the development of the community for the Chinese nation. In the societal transformation of the new era, the society should be a common construction of individual subjectivity and community for the Chinese nation. From this, a path of endogenous development which is suitable for our country's society should be explored, and Chinese path to modernization should also be continuously promoted. It is of great significance to study and explain the relationship between the community for the Chinese nation and the people's subjectivity for promoting Chinese path to modernization and building a community with a shared future for mankind.

Optimal zero-crossing group selection method of the absolute gravimeter based on improved auto-regressive moving average model

An absolute gravimeter is a precision instrument for measuring gravitational acceleration, which plays an important role in earthquake monitoring, crustal deformation, national defense construction, etc. The frequency of laser interference fringes of an absolute gravimeter gradually increases with the fall time. Data are sparse in the early stage and dense in the late stage. The fitting accuracy of gravitational acceleration will be affected by least-squares fitting according to the fixed number of zero-crossing groups. In response to this problem, a method based on Fourier series fitting is proposed in this paper to calculate the zero-crossing point. The whole falling process is divided into five frequency bands using the Hilbert transformation. The multiplicative auto-regressive moving average model is then trained according to the number of optimal zero-crossing groups obtained by the honey badger algorithm. Through this model, the number of optimal zero-crossing groups determined in each segment is predicted by the least-squares fitting. The mean value of gravitational acceleration in each segment is then obtained. The method can improve the accuracy of gravitational measurement by more than 25% compared to the fixed zero-crossing groups method. It provides a new way to improve the measuring accuracy of an absolute gravimeter.

Mechanical Properties and Crack Resistance of Basalt Fiber Self-Compacting High Strength Concrete: An Experimental Study.

Pure self-compacting concrete has many disadvantages, such as early shrinkage and cracking. The addition of fibers can effectively improve the properties of resistance to tension and cracking of self-compacting concrete, thereby the effect of improving its strength and toughness can be achieved. Basalt fiber is a "new green industrial material" that has unique advantages, such as high crack resistance and being lightweight compared with other fiber materials. In order to study the mechanical properties and crack resistance of basalt fiber self-compacting high-strength concrete intensively, the self-compacting high-strength concrete of C50 was designed and obtained using the absolute volume method with multiple proportions. Orthogonal experimental methods were used to study the influence of the water binder ratio, fiber volume fraction, fiber length, and fly ash content on the mechanical properties of the basalt fiber self-compacting high-strength concrete. Meanwhile, the efficiency coefficient method was used to determine the best experiment plan (water binder ratio 0.3, fiber volume ratio 0.2%, fiber length 12 mm, fly ash content 30%), and the effect of fiber volume fraction and fiber length on the crack resistance of the self-compacting high-performance concrete was investigated using improved plate confinement experiments. The results show that (1) the water binder ratio had the greatest impact on the compressive strength of basalt fiber self-compacting high-strength concrete, and as the fiber volume fraction increased, the splitting tensile strength and flexural strength both increased; (2) there was an optimal value for the effect of the fiber length on the mechanical properties; (3) with the increase in fiber volume fraction, the total crack area of the fiber self-compacting high-strength concrete significantly decreased. When the fiber length increased, the maximum crack width first decreased and then slowly increased. The best crack resistance effect was achieved when the fiber volume fraction was 0.3% and the fiber length was 12 mm. Therefore, basalt fiber self-compacting high-strength concrete can be widely used in engineering fields, such as national defense construction, transportation, and building structure reinforcement and repair, due to its excellent mechanical and crack resistance properties.

Research on the relationship between defense technology innovation and high‐quality economic development: Gray correlation analysis based on panel data

AbstractBased on panel data from 2010 to 2019, this study examines the relationship between defense science and technology innovation and high‐quality economic development at the provincial level in China. Using the gray correlation analysis method of panel data and an evaluation index system of high‐quality economic development, we calculate the gray correlation coefficient and decompose its time‐series gray correlation degree and cross‐sectional. Our findings indicate that the correlation between defense science and technology innovation and high‐quality economic development in China is generally stable during 2010–2019. However, Beijing stands out as an exception with a correlation coefficient of less than 0.5. Furthermore, there is regional gray correlation heterogeneity with the smallest correlation degree found in the eastern region and the largest in the northeast region. Based on our results, we propose three countermeasure suggestions: first, to balance national defense construction and economic construction; second, to optimize national defense science and technology strategy according to local conditions; and third, to effectively utilize industrial structure advantages. In summary, our study contributes to the literature by highlighting the relationship between defense science and technology innovation and high‐quality economic development in China. Our findings provide implications for policymakers and practitioners to make informed decisions in achieving sustainable and high‐quality economic development.

The influence of the selection of zero-crossing starting point on measurement accuracy of the absolute gravimeter

The absolute gravimeter is an important precision instrument for obtaining gravity acceleration in fields such as geophysics, resource survey, and national defense construction. It is greatly affected by its self-vibration during operation. If the self-vibration frequency exceeds the range of the sensor, it will not be effectively processed by the method of vibration compensation. To solve this problem, the effect of instrument self-vibration on the accuracy of gravity is analyzed through simulation and actual measurement data. Based on the calculation of the simulation data, the functional relationship between the self-vibration frequency of the instrument and the zero-crossing starting point is obtained. The Starting Point Mathematical Model is established to accurately calculate the zero-crossing starting point. Then, the zero-crossing starting point calculated by the model is taken as the time reference of the zero crossing for the least square fitting. The split and platform absolute gravity measurement systems are built, respectively, to test the measured data. The test results reveal that, compared with the traditional method using the initial falling time as the zero-crossing starting point, the proposed method can reduce the gravity deviation by 50 μGal and improve the accuracy by an average of 35.35% under split-type working conditions. Under platform-type working conditions, it can decrease the gravity deviation by 3 mGal and improve the accuracy by an average of 53.78%. The method proposed can reduce the fixed phase vibration interference caused by the instrument self-vibration and provide a reference for improving the measurement accuracy of the instrument under different working conditions.

Multiview Fusion 3D Target Information Perception Model in Nighttime Unmanned Intelligent Vehicles

Unmanned technology is an important development project of today’s cutting-edge science and technology, which has a significant impact on social and economic development, national defense construction, and scientific and technological development. The rapid development of industrial information technology has driven the unmanned intelligent vehicle system to innovate and gradually enter the public’s view, and at the same time, the driving safety of unmanned intelligent vehicles is also widely concerned. Target information perception system is the foundation of unmanned system and the fundamental guarantee of safety and intelligence of unmanned vehicles. There are three key problems of target recognition in unmanned driving, namely, target classification, localization, and attitude determination. In the implementation of a networked virtual environment system, a flexible and complete perception model is needed as the guiding model of the system. Since 3D point cloud data can provide more spatial information than 2D RGB image data, it is more beneficial to determine the target category, position, and pose in 3D. In this paper, based on the existing research of unmanned intelligent vehicle perception system, we combine the application of fusion of 3D target information perception model and develop a nighttime unmanned system based on multiview fusion of 3D target information perception model. This system can simultaneously perform the detection of multiple categories of objects and predict the center point, length, width, height, and orientation of the objects, so that the unmanned car can sense the location of the surrounding objects when driving in the actual scene.

Processes of the Reliability and Degradation Mechanism of High-Power Semiconductor Lasers

High-power semiconductor lasers have attracted widespread attention because of their small size, easy modulation, and high conversion efficiency. They play an important role in national economic construction and national defense construction, including free-space communication; industrial processing; and the medical, aerospace, and military fields, as well as other fields. The reliability of high-power semiconductor lasers is the key point of the application system. Higher reliability is sought in the military defense and aerospace fields in particular. Reliability testing and failure analysis help to improve the performance of high-power semiconductor lasers. This article provides a basis for understanding the reliability issues of semiconductor lasers across the whole supply chain. Firstly, it explains the failure modes and causes of failure in high-power semiconductor lasers; this article also summarizes the principles and application status of accelerated aging experiments and lifetime evaluation; it also introduces common techniques used for high-power semiconductor laser failure analysis, such as the electron beam-induced current (EBIC) technique and the optical beam-induced current (OBIC) technique, etc. Finally, methods used to improve the reliability of high-power semiconductor lasers are proposed in terms of the preparation process, reliability screening, and method application.

Experimental Study on the Salt Freezing Durability of Multi-Walled Carbon Nanotube Ultra-High-Performance Concrete.

Ultra-high-performance concrete (UHPC) is a new type of high-performance cement-based composite. It is widely used in important buildings, bridges, national defense construction, etc. because of its excellent mechanical properties and durability. Freeze thaw and salt erosion damage are one of the main causes of concrete structure failure. The use of UHPC prepared with multi-walled carbon nanotubes (MWCNTs) is an effective method to enhance the durability of concrete structures in complex environments. In this work, the optimal mix proportion based on mechanical properties was obtained by changing the content of MWCNTs and water binder ratio to prepare MWCNTs UHPC. Then, based on the changes in the compressive strength, mass loss rate, and relative dynamic modulus of elasticity (RDME), the damage degree of concrete under different salt erosion during 1500 freeze-thaw (FT) cycles was analyzed. The changes in the micro pore structure were characterized by scanning electron microscope (SEM) and nuclear magnetic resonance (NMR). The test results showed that the optimum mix proportion at the water binder ratio was 0.19 and 0.1% MWCNTs. At this time, the compressive strength was 34.1% higher and the flexural strength was 13.6% higher than when the MWCNTs content was 0. After 1500 salt freezing cycles, the appearance and mass loss of MWCNTs-UHPC prepared according to the best ratio changed little, and the maximum mass loss was 3.18%. The higher the mass fraction of the erosion solution is, the lower the compressive strength and RDME of concrete after FT cycles. The SEM test showed that cracks appeared in the internal structure and gradually increased due to salt freezing damage. However, the microstructure of the concrete was still relatively dense after 1500 salt freezing cycles. The NMR test showed that the salt freezing cycle has a significant influence on the change in the small pores, and the larger the mass fraction of the erosion solution, the smaller the change in the proportion of pores. After 1500 salt freezing cycles, the samples did not fail, which shows that MWCNTs UHPC with a design service life of 150 years has good salt freezing resistance under the coupling effect of salt corrosion and the FT cycle.

<i>In situ</i> X-ray diffraction measurement of shock melting in vanadium

The solid-liquid phase transition under shock wave loading in materials is called shock melting. Shock melting is important not only in fields like high pressure EOS or material dynamic response, but also in applications like device protection in modern industry and national defense construction. The obtaining of precise melting curve is more than understanding the high pressure melting behavior, and it can provide the reliable evidence for the theoretical model of melting mechanism. So the solid-liquid phase transition under extreme conditions is a research hotspot, and a lot of researches have been carried out. But, the enormous discrepancy between the melting curve of dynamic loading and hydrostatic loading in transition metals, especially, the vanadium has been unclear for decades. The difference in melting temperature under 200 GPa between dynamic loading and hydrostatic loadirng is as large as twice (about 4000 K). Recently, Errandonea and Zhang’s experiments present a new insight into this discrepancy, indicating that the new shock melting curve is consistent with the extrapolated melting curve contained by LH-DAC. But all the dynamic loading experimental data are measured by macroscopic quantities; they can determine the occurrence of the phase transition, but cannot provide the microscopic structure of the material under extreme conditions. So, as the technic of in situ X-ray diffraction has developed well in recent years, we use the high power laser driving technic combining with in situ X-ray diffraction measurement to explore the structure of vanadium near the melting line. We measure the micro structure of vanadium at up to 200 GPa in shock experiment for the first time. We find that the bcc phase transition is not observed at around 60 GPa, which is different from previous experiments in DAC or gas gun loading experiments, but consistent with Chen’s leaser driving experiment. The result confirms that when the impact pressure is 155 GPa, vanadium still remains solid BCC phase. It becomes liquid at about 190 GPa. In contract to Zhang’s results, the DXRD melting point is consistent with the new melting line. This work provides the evidence of the consistency of shock and hydrostatic melting curve, confirming the phase boundary of vanadium under 200 GPa. This work has important scientific significance in understanding the pressure melting behavior of transition metals. The method in this work can be applied to the research of melting properties of other materials.

Fine-Grained Recognition for Oriented Ship Against Complex Scenes in Optical Remote Sensing Images

Remote sensing ship recognition is widely used in civil and military applications, such as national defense construction, fishery management, and navigation supervision. Unfortunately, limited by the lack of public datasets for fine-grained ship recognition, current studies mainly focus on ship detection or coarse-grained ship recognition, whereas fine-grained recognition task is left out. The main challenges for fine-grained ship recognition include: 1) complex scenes and 2) ship characteristics of arbitrary orientation, dense distribution, and huge scale and appearance variation. Aiming at the challenges above, we propose a novel efficient information reuse network (EIRNet) and establish a public 20-class Dataset for Oriented Ship Recognition (DOSR). In our EIRNet, considering recognition robustness to multiscale ships, a dense feature fusion network (DFF-Net) with two fusion directions is designed to maximize the utilization of multilayer information and reduce information redundancy. Then, the fused feature maps are refined by a dual-mask attention module (DMAM) to improve performance in dense and clutter scenes by enhancing the distinction between ships and suppressing clutter. Furthermore, Mask-RPN improves the efficiency of generating proposals by reusing the attention mask. Finally, we introduce a concept of upper level class to mine interclass relationships, which further improves the recognition accuracy. Extensive experiments demonstrate that our EIRNet achieves state-of-the-art performance on DOSR and another popular public dataset called HRSC2016.

High-Quality Development Strategy for the Supply Chain of Critical Minerals and Its Material Industry in China

Critical minerals and materials are fundamental to national economy, national defense construction, and residents’ lives; therefore, it is of great significance to ensure the stability of their supply chain. This study associates mineral resources with thematerial industry and analyzes the strategic needs and development status of China’s key minerals and their raw material industries from the perspective of the entire industrial chain including resource exploration, mining, smelting, material processing, manufacturing, and product recycling. Moreover, problems are summarized including blocked industrial chain; insufficient supply of key minerals at the resource end; high energy consumption and excessive scale at the smelting end; insufficient support capacity, inadequate innovation ability, and weak industrial foundation at the material end; and lagging development at the recycling end. Focusing on exploration, mining, and basic raw material preparation, a three-step goal by 2035 is proposed, and technological development priorities are summarized from the aspects of mining, smelting, and basic raw materials. Furthermore, we propose suggestions for the high-quality development of China’s key minerals and material industry supply chain, including promoting the supply guarantee capacity of domestic mineral resources, improving the technical competitiveness of new materials, and unblocking the resource–smelting–material–recycling industrial chain.

Intelligent Model Library for Nonferrous Metal Industry: Construction Method and Application

Nonferrous metal industry is the foundation of China’s substantial economy and plays a key role in national economy and defense construction. Industrial software is crucial for the high-quality development of the nonferrous metal industry and is associated with the in-depth implementation of national software development strategies. Currently, the industrial software development in the nonferrous metal industry is significantly restricted by the lack of knowledge models. Hence, we propose a method for constructing an intelligent model library for the nonferrous metal industry. Considering meta-model-driven engineering, we define the nonferrous metallurgical meta-model and its attributes, and propose a meta-modeling method based on the MODELING architecture. Additionally, we design an overall architecture for the intelligent model library based on industrial Internet, an agile model-development environment integrating multiple languages, and a meta-model encapsulation system based on multi-scenario black-box reuse. Moreover, a meta-model full lifecycle management platform is constructed based on a five-layer two-dimension classification standard and the domain knowledge graph. The intelligent model library for the nonferrous metal industry is developed based on the long-term accumulation of nonferrous metallurgy process mechanism, operating experiences, and intelligent methods. The good role of intelligent model library in improving the intelligent level in engineering applications is presented through the application of two typical nonferrous metallurgical scenarios. The intelligent model library of the nonferrous metal industry provides a core knowledge support for the development of industrial software and plays a fundamental role in promoting smart manufacturing and strengthening the nonferrous metal industry.

The Development and Innovation of the First Supercomputer YH-1 in China: From the Perspective of Technology History

China’s first supercomputer capable of 100 million calculations per second was the YH-1, which was independently developed by the Institute of Computer Science at the National University of Defense Technology (NUDT) between 1978 and 1983. YH-1 played an important role in China’s national defense construction and national economic development. It made China one of the few countries in the world to successfully develop a supercomputer. Based on original archive documents, interviews with relevant personnel, and an analysis of the technological parameters of the supercomputers YH-1 in China and Cray-1 in the United States, this paper reviews in detail the historic process of the development of YH-1, analyzing its innovation and summarizing the experience and lessons learned from it. This analysis is significant for current military-civilian integration, and the commercialization of university research findings in China.

Application of Intelligent Manufacturing Technology in the Field of Ship Design and Manufacturing

With the rapid development of information technology and its gradual penetration into the traditional manufacturing industry, modern industry has entered a period of intelligent manufacturing. In order to firmly grasp this brand-new development opportunity, various industries in our country are accelerating innovation and development, forming a number of brand-new industries and models. At this stage, the global shipping volume is increasing slowly and the endogenous power is lacking. The shipbuilding industry occupies a large proportion of my country’s traditional industries. It not only provides technical equipment for the development of marine resources and national defense construction, but is also an important channel for world trade, driving the development of many key industries, and it is a modern comprehensive industry with a huge industrial chain. Sex industry. The shipbuilding industry can drive the rapid development of the local economy and play an important role in promoting labor employment and ensuring the safety of coastal defense. In recent years, my country’s foreign trade has been growing at an alarming rate, which has provided better development opportunities to a certain extent. The industry has high international competitiveness.

Constructing artificial neural networks using genetic circuits to realize neuromorphic computing

With the advent of the era of big data, existing computing systems limit the development of new technologies such as cloud computing and artificial intelligence. As the demand for high-performance computing continues to grow, traditional computing models are facing unprecedented challenges. Neural mimicry computing based on artificial neural networks provides a potential solution, and biological computing with advantages such as low energy consumption parallelization is very important for its research, in which gene circuitry will be the key to the construction of artificial neural networks. In this study, we used biological elements to construct gene circuits to form neural network structures to realize neural mimicry calculations. Based on the similarity between the structure of gene circuits and neural networks, we describe a neural network design based on the logic gate calculation of gene circuits, and realize the applications of linear classification, nonlinear classification and pattern classification. In the linear classification of NAND, the four datasets in the space are divided into two categories by hyperplane. The structural design of the neural network for linear classification can be realized by using the genetic circuit, which includes five biological elements and the biological elements between different layers are connected by gene regulation. The simulation results of linear classification showed that the gene circuit realizes the function of NAND by means of the neural network and the output fluorescence value as the detection standard. In the nonlinear classification of XOR, the four datasets in the space are divided into two categories. The structural design of the neural network for nonlinear classification can be realized by using the genetic circuit, which includes six biological elements. The simulation results of nonlinear classification showed that the gene circuit realizes the function of XOR by means of the neural network and the output fluorescence value as the detection standard. In the pattern classification, the neural network with five layers and eight neurons was constructed by a genetic circuit with eight biological elements connected by gene regulation. The simulation results of pattern classification showed that the gene circuit realizes the function of pattern classification by means of the neural network and the output fluorescence value as the detection standard. This study realizes neural mimicry computing by constructing neural network through engineering gene circuits. The integrated molecular computing system is expected to be applied to the manufacturing of artificial intelligence chips, and further applied to aerospace, information security and national defense construction, along with other fields.

QUALITY INSPECTION FOR BLOCK ADJUSTMENT OF THE ZY3 STEREO SATELLITE IMAGERY

Abstract. 3D modeling and DEM results have played an important role in economic construction, national defense construction, social development, and ecological protection. And the regional network adjustment is the basic work of DEM, and 3D modeling. In order to ensure the quality of the following results, this paper selects the regional network adjustment results of the ZY3 stereo satellite image and puts forward the test method of the regional network adjustment results from the inspection content. Meanwhile, the northwest of Africa is selected as the test area, and the inspection contents and methods proposed in this paper are verified. The inspection results show that the quality problems existing in the adjustment results of the regional network can be effectively checked. It has a certain reference function to the quality problem of the production process.

Research on Stable Motion Control Method of Underwater Robot Based on Collaborative Filtering Technology

As countries in the world continue to deepen marine research and development and the need for national defense construction, unmanned underwater robots are playing an increasingly important role in scientific experiments, seabed oil and gas exploration and testing, and military affairs. The motion stability of underwater robots is the key to ensure the safe and reliable operation of underwater robots, and it is the main content of stability control research to make underwater robots return to the initial state of motion after being disturbed. Therefore, it becomes very important to study stability control methods. It’s necessary. This thesis first analyzes the motion characteristics of collaborative filtering technology in water, and establishes a dynamic model of an underwater robot system composed of main thrusters, double vertical thrusters and double-sided thrusters, and performs basic fluid flow for underwater robots.

A novel geomagnetic assimilation method of vector geomagnetic data

Geomagnetic field has important applications in Earth Science, earthquake prediction, aerospace, national defense construction and other areas. Therefore, accurate modeling of regional geomagnetic field is very important. Geomagnetic assimilation method can effectively improve the accuracy of regional vector geomagnetic data, and then promote the establishment of high-precision geomagnetic regional model. The geomagnetic stations at different latitudes and longitudes have different influences on the geomagnetic assimilation of vector geomagnetic data. However, traditional geomagnetic assimilation methods do not take into account the differences in latitude and longitude, which result in low accuracy of the geomagnetic assimilation of vector geomagnetic data. To solve the problem, this paper proposes a new geomagnetic assimilation method based on the three weighting factors of direction, distance and a parameter k. In this method, the longitude differences and latitude differences of different stations are taken as the weight elements to participate in the weight determination, and parameter k is set to further modify the weight, so as to achieve the high precision geomagnetic assimilation to regional vector geomagnetic data. Based on the real observation data of five stations in the European region of station network in the world data center (WDC), this paper conducted geomagnetic assimilation of the vector geomagnetic data of different stations. The experimental results show that at five stations which include some central stations and some marginal stations, for the F, H, D and I geomagnetic elements, the geomagnetic assimilation accuracy of the proposed method is better than that of the method based on the distance weighting method both on magnetically quiet day and on magnetically disturbed day. In addition, the results also show that the geomagnetic assimilation accuracy of FUR station, which is a marginal station, is significantly improved by the proposed method. On magnetically disturbed day, the error of F component is reduced by 0.6 nT, and the error of H component is reduced by 1 nT. On magnetically quiet day, the error of F component is reduced by 0.4 nT, and the error of H component is reduced by 0.1 nT. The above results prove the effectiveness and feasibility of the proposed method in the geomagnetic assimilation of vector geomagnetic data, especially for the vector geomagnetic data of marginal area.

Research on Optimization of Carbon Emission Reduction of Coal Supply Chain System in Iron and Steel Industry

The steel industry is an important basic industry for the development of the national economy and national defense construction, but it is also a major source of energy consumption and environmental pollution. In particular, the carbon emissions in the process of coal combustion and steelmaking are huge. This situation urgently needs to be improved and optimized. Therefore, based on the perspective of the coal supply chain in the steel industry, this paper constructs a multi-objective planning model to achieve a balanced optimization of total economic costs and carbon emission reduction, and verifies the effectiveness of the model through specific case data. This paper sets three different emission reduction scenarios, discusses and analyzes the changes of economic total cost and carbon emission under different emission reduction scenarios, and finds that suppliers with good coal mining technology and low carbon emission factor have more opportunities to be selected and can obtain more coal market orders. At the same time, steel plants with mature processing technology and low carbon emission factor can further gain market competitive advantage and undertake more steelmaking tasks. Finally, based on results, management suggestions for coal suppliers and steel plants are provided.