Modern Coal Research Articles

Artificial Intelligence, data protection and medical device regulations: squaring the circle with a historical perspective in Europe

PurposeThis manuscript presents a parallel among important EU legal frameworks, such as the Medical Device Regulations and General Data Protection Regulation and economic-historical challenges faced by European citizens. This parallel offers a prospective for understanding the direction taken by policymakers for forthcoming regulations, such as the European Health Data Space and the AI-Act.MethodThe paper describes key commonalities and differences among those regulations, which may help scholars working with AI in medicine, navigating this articulated legal framework.ResultsThe European Union journey started with the European Coal and Steel Community, enforced after the WWII for nurturing European physical reconstruction and as a mean for peacekeeping: without coil it was not possible to transform steel, and with shared control of steel it was not possible for individual member states to build war weapons.ConclusionsIn this century, modern coal are data and modern steel is the AI, which is a crucial enabler for European economy growth and competitiveness, and, potentially, a powerful war weapon. Ensuring a fair data-sharing and correct use of AI is crucial for sustainable development, peace, and democracy in Europe and beyond.

Fostering the National Interest: Utilizing Hungarian State Property in the Jiu Valley to Build a Modern Coal Industry

Abstract After the 1867 Ausgleich, the Kingdom of Hungary sought to foster coal extraction to fuel the growing needs of transport and industrialization. In developing the rich deposits of the Jiu Valley in Transylvania, the state did not wait for private, profit-driven development. Instead, the ministries in Budapest both developed state-operated mines in the region and supported private companies’ efforts, shifting the relative importance of each over the following four decades as the situation required. The ministries worked with private corporations to design model “company towns” and provided consistent support for their upkeep—demonstrating the extensive nature of state influence at the local level. The Jiu coal mines as a case study reflect that the Hungarian state saw property not simply in economic terms but as part of a wider framework of the modernization of the country, including its society. Royal Hungary’s property regime was one that provided legal recognition of the right to private property, but at the same time one in which the state frequently intervened to ensure economic development that served its perceived interests.

Multi-scale coal and gangue detection in dense state based on improved Mask RCNN

Coal and gangue intelligent sorting accounts for a vital proportion of modern coal mines, which takes on critical significance in boosting clean coal utilization. Aiming at the problem of low recognition accuracy that arises from the large diversity in particle size of raw coal and the adhesion and half-occlusion between them, A Mask RCNN-based instance segmentation network for coal and gangue image is proposed. First, multi-branch parallel feature extraction bottlenecks are developed to build a lightweight backbone with a mixed attention mechanism and self-correcting convolution incorporated to enhance the feature representation of targets. Subsequently, a necknet is developed, aggregating the context feature information of the backbone from channel and space to enhance the position and boundary information of targets. Lastly, the effectiveness of this method is fully validated by ablation and test experiments using self-built coal and gangue RGB image datasets include varieties of characteristics as input. As indicated by the experimental results, the above-described method is capable of enhancing the segmentation ability of stacked and adhered coal and gangue and reducing the missed detection rate of small targets. ISNet_CG achieves mAP, mIoU, F1-scores, and FPS of 98.0, 96.5, 0.987, and 24.2 FPS, respectively, such that the correct category and location can be provided for coal and gangue in a dense state.

Monitoring Mining Surface Subsidence with Multi-Temporal Three-Dimensional Unmanned Aerial Vehicle Point Cloud

Long-term and high-intensity coal mining has led to the increasingly serious surface subsidence and environmental problems. Surface subsidence monitoring plays an important role in protecting the ecological environment of the mining area and the sustainable development of modern coal mines. The development of surveying technology has promoted the acquisition of high-resolution terrain data. The combination of an unmanned aerial vehicle (UAV) point cloud and the structure from motion (SfM) method has shown the potential of collecting multi-temporal high-resolution terrain data in complex or inaccessible environments. The difference of the DEM (DoD) is the main method to obtain the surface subsidence in mining areas. However, the obtained digital elevation model (DEM) needs to interpolate the point cloud into the grid, and this process may introduce errors in complex natural topographic environments. Therefore, a complete three-dimensional change analysis is required to quantify the surface change in complex natural terrain. In this study, we propose a quantitative analysis method of ground subsidence based on three-dimensional point cloud. Firstly, the Monte Carlo simulation statistical analysis was adopted to indirectly evaluate the performance of direct georeferencing photogrammetric products. After that, the operation of co-registration was carried out to register the multi-temporal UAV dense matching point cloud. Finally, the model-to-model cloud comparison (M3C2) algorithm was used to quantify the surface change and reveal the spatio-temporal characteristics of surface subsidence. In order to evaluate the proposed method, four periods of multi-temporal UAV photogrammetric data and a period of airborne LiDAR point cloud data were collected in the Yangquan mining area, China, from 2020 to 2022. The 3D precision map of a sparse point cloud generated by Monte Carlo simulation shows that the average precision in X, Y and Z directions is 44.80 mm, 45.22 and 63.60 mm, respectively. The standard deviation range of the M3C2 distance calculated by multi-temporal data in the stable area is 0.13–0.19, indicating the consistency of multi-temporal photogrammetric data of UAV. Compared with DoD, the dynamic moving basin obtained by the M3C2 algorithm based on the 3D point cloud obtained more real surface deformation distribution. This method has high potential in monitoring terrain change in remote areas, and can provide a reference for monitoring similar objects such as landslides.

Production management system in a modern coal and coke company based on the demand and quality of the exploited raw material in the aspect of building a service-oriented architecture

The paper deals with the implementation of the JSW Capital Group’s (Poland) Demand and Quality Driven Production Management System (SPPJ – System Zarządzania Produkcją oparty na Popycie i Jakości) using a service-oriented architecture (SOA). The main components of the SPPJ architecture have been characterized, and the scope of their integration has been defined. The individual parts in the first area, i.e. quality management, have been described in detail. Due to the extensive nature of the issue, components in other areas, i.e. planning and scheduling, coal extraction and processing, coke production, as well as sales and logistics, have only been signalled. Results of the analysis of the implementation of particular components of SPPJ areas have also been presented. The development of the system and the way of implementation in a mining environment is important from the perspective of achieving the superior objective of the JSW Capital Group’s Quality Programme, which is to increase the efficiency of management of the exploited deposit and the volume of commercial product supply.

Joint berth allocation and ship loader scheduling under the rotary loading mode in coal export terminals

Due to nonmatching between the efficiency of ship deballasting and terminal loading, operations in modern coal export terminals (CETs) are frequently interrupted and significantly restricted by ship deballasting delays. This paper addresses a novel integrated problem of berth allocation and ship loader scheduling arising in CETs with new features, including the symmetrical berth layout-based rotary loading mode (SBLRLM) and deballasting restrictions. A mixed-integer programming (MIP) model is proposed to make joint decisions to minimize the total tardiness of all ships. By exploring the problem's decomposable structure, an exact method that relies on logic-based Benders decomposition (LBBD) is proposed to obtain optimal solutions. According to the problem features, the monolithic MIP formulation is decomposed into a new MIP (master problem) and a constraint programming (subproblem). Combinatorial valid inequalities are developed to enhance the master problem model and obtain a tighter lower bound. A Benders cut strengthening heuristic is developed to generate feasibility and optimality cuts to ensure efficient algorithm convergence. To evaluate the proposed method, computational experiments are conducted on a set of test instances generated based on real data collected from a major CET in northern China. The results indicate that the LBBD algorithm can optimally solve large-scale problem instances within a reasonable amount of time. The plan generated by the LBBD algorithm achieves a 51.9% reduction in ship tardiness, on average, compared to that of practical scheduling methods. By using the proposed method, the superiority of the SBLRLM in reducing deballasting delays becomes more significant as the problem scale increases. In addition, considering different working intensities, the results could also help port operators make decisions about the number of berths in the SBLRLM.

Application Analysis of Frequency Conversion Technology in Modern Coal Mine Electromechanical Engineering

Application Analysis of Frequency Conversion Technology in Modern Coal Mine Electromechanical Engineering

Research on Ventilation Reliability and Safety Production in Modern Coal Mines

Research on Ventilation Reliability and Safety Production in Modern Coal Mines

Research on the Technology of Zero Discharge of Waste Water in Modern Coal Chemical Enterprises

Research on the Technology of Zero Discharge of Waste Water in Modern Coal Chemical Enterprises

Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not?

(1) Background: As a world-recognized high-risk occupation, coal mine workers need various cognitive functions to process the surrounding information to cope with a large number of perceived hazards or risks. Therefore, it is necessary to explore the connection between coal mine workers’ neural activity and unsafe behavior from the perspective of cognitive neuroscience. This study explored the functional brain connectivity of coal mine workers who have engaged in unsafe behaviors (EUB) and those who have not (NUB). (2) Methods: Based on functional near-infrared spectroscopy (fNIRS), a total of 106 workers from the Hongliulin coal mine of Shaanxi North Mining Group, one of the largest modern coal mines in China, completed the test. Pearson’s Correlation Coefficient (COR) analysis, brain network analysis, and two-sample t-test were used to investigate the difference in brain functional connectivity between the two groups. (3) Results: The results showed that there were significant differences in functional brain connectivity between EUB and NUB among the frontopolar area (p = 0.002325), orbitofrontal area (p = 0.02102), and pars triangularis Broca’s area (p = 0.02888). Small-world properties existed in the brain networks of both groups, and the dorsolateral prefrontal cortex had significant differences in clustering coefficient (p = 0.0004), nodal efficiency (p = 0.0384), and nodal local efficiency (p = 0.0004). (4) Conclusions: This study is the first application of fNIRS to the field of coal mine safety. The fNIRS brain functional connectivity analysis is a feasible method to investigate the neuropsychological mechanism of unsafe behavior in coal mine workers in the view of brain science.

МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ДЛЯ РАЗРАБОТКИ ТЕХНОЛОГИЧЕСКОЙ ЛИНИИ ПО ПРОИЗВОДСТВУ ГУМИНОВЫХ УДОБРЕНИЙ НА ОСНОВЕ МОДУЛЬНОГО ОБОРУДОВАНИЯ

The development of organic agricultural production in Russia is hampered by the lack of the necessary organic fertilizers as modern technological lines processing peat, brown coal, sapropel, and biohumus are still unavailable. Because of the need for such technological lines, a mathematical model has been developed to describe the hydromechanical and mechanical processes, enabling operators to select the operating mode parameters of the technological line. For the first time, the proposed model can be used to form a suspension with the required fineness in a hydromechanical cleaner and reactor. The authors propose a technique for assembling technological lines based on modular equipment to process organic raw materials that ensures the industrial productivity and quality of humic fertilizers. It is shown that the presented mathematical model fully complies with the real technological production requirements and can be used for theoretical and engineering analysis. The mathematical model of the technological line processing organic raw materials is based on the theory of artificial neural networks. The model can be further improved to be used in the system for automatizing technological operations and monitoring the quality indicators of modular equipment in the processing of organic raw materials. This will provide a new level of synthesizing complex technical systems, which will be beneficial for agricultural roduction.

Designing coal preparation circuit for cleaning high ash and high sulfur Punjab (Pakistan) coal to meet end-user requirements

ABSTRACT Modern coal preparation plants are designed to achieve maximum overall clean coal yield with an acceptable amount of impurities to meet end-user requirements. LIMN is commonly used to design and simulate coal processing circuits based on size and density distribution data of coal. In this study, particle distribution data for size, density, and floatability were established for Punjab coal after crushing it to 38 mm. Punjab coal contains high amounts of ash (34.70%) and sulfur (8.34%). Float-sink tests conducted on several size fractions disclosed that 16% target ash could be achieved at an overall yield of 63% with ash and sulfur rejection values in the range of 72.63–94.18% and 73.01–88.45%, respectively. However, the sulfur limit of 1.0% would be difficult to meet. Dell release analysis performed on – 0.25 mm fraction revealed poor flotation response of Punjab coal. Several process flowsheets were designed and simulated using LIMN to generate data for yield, ash and sulfur. End-User Beneficiation Number (EBN) was introduced and utilized for determining the best processing option that can provide maximum yield while meeting the quality requirements of the end-user. Economic analysis involving CAPEX, OPEX, and payback period validated the merit of EBN.

Improving Coal Quality Estimations with Geostatistics and Geophysical Logs

In most modern coal mines, there are many coal quality parameters that are measured on samples taken from boreholes. These data are used to generate spatial models of the coal quality parameters, typically using inverse distance as an interpolation method. At the same time, downhole geophysical logging of numerous additional boreholes is used to measure various physical properties but no coal quality samples are taken. The work presented in this paper uses two of the most important coal quality variables-ash and volatile matter-and assesses the efficacy of using a number of geostatistical interpolation methods to improve the accuracy of the interpolated models, including the use of auxiliary variables from geophysical logs. A multivariate spatial statistical analysis of ash, volatile matter and several auxiliary variables is used to establish a co-regionalization model that relates all of the variables as manifestations of an underlying geological characteristic. A case study of a coal mine in Queensland, Australia, is used to compare the interpolation methods of inverse distance to ordinary kriging, universal kriging, co-kriging, regression kriging and kriging with an external drift. The relative merits of these six methods are compared using the mean error and the root mean square error as measures of bias and accuracy. The study demonstrates that there is significant opportunity to improve the estimations of coal quality when using kriging with an external drift. The results show that when using the depth of a sample as an external drift variable there is a significant improvement in the accuracy of estimation for volatile matter, and when using wireline density logs as the drift variable there is improvement in the estimation of the in situ ash. The economic benefit of these findings is that cheaper proxies for coal quality parameters can significantly increase data density and the quality of estimations.

Analysis of Current Situation and Trend of Modern Coal Chemical Technology

The rapid development of modern coal chemical enterprises and progress in the technical research and application demonstrate the great potential of the industry. For example, they have been strong performers in manufacturing substitute natural gas, coal-to-liquids and coal-based chemicals, boosting demands for its products. The scale of medium and large enterprises indicates a satisfied overall situation with promising future. The paper discussed the technical development of the modern coal chemical industry in general and the future of the industry.

Estimation of a possibility to transform a technological complex of the liquidated coal mine into the data processing center (data-center)

Today, in order to develop a contemporary society, assimilation of the necessary knowledge and organization of information storage, processing and use are the vital tasks. For this purpose, information data centers are being created, which ensure the realization of these tasks at all levels - from national to individual. Accordingly, location, volume and operation speed of the data centers are changing. Any data center is a fairly costly enterprise, building it "from scratch" requires significant material investments and human resources. Therefore, today researches are aimed at reusing areas and buildings of the out-of-date enterprises and organizations with the exhausted resources, but which, due to the acceptable rate of wear and tear, can be transformed into the innovative enterprises. In Ukraine, it is planned to close a number of coal mines, and, as a result, a significant number of industrial areas suitable for the renovation use will be vacated. Organization of a data center based on the existing facilities of the liquidated coal mine is quite possible and advisable; information about this is given in the article. There are many examples (for example, the Europe's largest data center Lefdal Mine Datacenter in Norway) of the data centers created on the basis of the liquidated industrial enterprises which, after their appropriate adaptation and modification, meet all requirements of the international standard ANSI/TIA/EIA-942. In Ukraine, there are also similar projects (for example, the United DC data center), which can be effectively introduced into the infrastructure of any industrial enterprise to be liquidated. The authors of this article have proven that modern coal mines (in particular, their surface technological complex) are essentially suitable for transformation into a data center due to the existing engineering and transport infrastructure, their favorable location and the required protection. The authors also provide information about the structure of the data center, audit of the surface complex in order to determine "bottlenecks" (non-compliance with the requirements of the ANS/TIA/EIA-942 standard), prerequisites for creating a data center on its basis, principles of calculating degree of depreciation of buildings and areas required for data center layout.

Determination of the Parameters of Technological Schemes for the Development of Coal Seams Prone to Spontaneous Combustion using Computer Simulation

The study considers thr problem of endogenous fire hazard in underground mining of coal seams prone to spontaneous combustion. The main trends in the development of modern technology of underground coal mining are shown. The interaction of air-gas-dynamic and geomechanical processes in the development of coal seams by longwall mining is considered. The possibilities of computer simulation of air-gas-dynamic processes in the extraction districts of modern coal mines are considered. The significant influence of geological and mining conditions of mining operations on the distribution of air flow in extraction districts and the efficiency of gas emission control in the workings of the extraction districts are shown. The design scheme and the results of numerical studies (methane and oxygen concentration fields) are given. It is concluded that it is necessary to determine the rational parameters of the preparation, ventilation, isolated drainage and degassing schemes when developing gas-bearing coal seams that are prone to spontaneous combustion. Recommendations are given on improvement of the safety in mining coal seams that are prone to spontaneous combustion.

A hybrid intelligent optimization approach to improving quality for serial multistage and multi-response coal preparation production systems

Modeling and optimization of multiple quality response characteristics (i.e., ash content and calorific value) has been a very important issue that can assure the quality conformance and stability for coal preparation system with multiple operating stages. Although extensive research works have been reported on multistage and multiple responses optimization problem, the traditional physical based model and statistical cause-effect model reaches its limits due to the fast increasing complexity, nonlinearity and high-dimensionality of modern coal preparation system. In addition, these conventional modeling and optimization methods have poor self-adaption and self-learning ability to different operation conditions. Internet-of-things and cyber manufacturing techniques make it convenient to collect larger volumes of sensor data that can provide powerful support for efficient data analytics. The combination of massive industrial data, advanced machine learning models and intelligent optimization algorithms bring new opportunities to deal with these problems. Therefore, this paper attempts to propose a hybrid intelligent technique based multistage and multi-response optimization approach for serial coal preparation system. Firstly, using the support vector regression theory, we construct a mechanism-data hybrid driven and forward-iteration model to reflect the change and propagation mechanism of quality response characteristics along the stage. Secondly, combining with the constructed response models and modified desirability function, the genetic algorithm based backward-iteration optimization search method is presented to determine the globally best processing setting conditions. A real life case study is used to verify the usefulness of proposed approach. Additionally, the performance of surrogate models based on different propagation modeling mode, kernel parameter optimization methods and modeling techniques are comprised and discussed. The results show the effectiveness and superiority of proposed approach.

Potential methanol-ethanol synthesis from Hungarian sub-bituminous coal via plasma gasification and Fischer-Tropsch synthesis

A possible way of coal processing in Hungary with clean coal technology is detailed in this paper. First, the situation of coal mining in Hungary is introduced. Then a possible method for the utilisation of the Hungarian coal reserves is described: syngas is produced in a modern plasma coal gasifier which is utilised in a catalysed Fischer-Tropsch reactor to form oxygenates. The primary products of this process are alcohols: considering the obtained 53.8-97.2% coal gasification efficiency and the 2.5-6.3% alcohol production efficiency, 144.7-467.5 kg alcohol (methanol, ethanol) can be synthesised from 10 tons of sub-bituminous Borsod coal with clean coal technology. These oxygenates can be considered as high added value, environmentally friendly fuel additives which increase the octane number of gasoline. The experimental results obtained in the laboratory and at pilot-plant scale are discussed along with estimations concerning the feasibility of the novel technology. [Received: April 1, 2017; Accepted: December 24, 2017]

Systematic study of the effect of particle density distribution on the flow and performance of a dense medium cyclone

Dense medium cyclone (DMC) is widely used to upgrade run-of-mine coal in modern coal preparation plants. The flow within it is very complicated, with multi-phases involved including air, water, coal and magnetic/non-magnetic particles of different sizes, densities and other properties. In this work, the effect of coal particle density distribution, one of the most important variables and highly related to coal type, is systematically studied using a combined approach of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM). In particular, the so called Johnson's SB function, which can describe a wide range of distributions, is employed to represent different particle density distributions. For a given density range, the function is characterized by two parameters: median particle density ρ0.5 and distribution parameter σj, with the latter describes the spread of the distribution. The effects of the two parameters on the flow and performance of a typical DMC are quantified. Moreover, their implication to practical operation, e.g. when the amount of near gravity material is high, is discussed. The results are also analysed in terms of the medium and particle flow fields, particle-fluid, particle-particle and particle-wall interaction forces to understand the fundamentals of the operation. The results obtained in this work should be useful to the design and control of DMC operations with different coal density distributions or coal types.

The development of modern coal technologies in Kyrgyzstan

The development of modern coal technologies in Kyrgyzstan