Predicting the yield of coke-plant products on the basis of petrographic analysis

Danilov, A. B.; Verdibozhenko, G. S.; Drozdnik, I. D.; Мірошниченко, Д. В.; Kaftan, Yu. S.; Golovko, M. B.

doi:10.3103/s1068364x1211004x

Cited by 11 publications

(2 citation statements)

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“…This is consistent with data from S. G. Gagarin, M. B. Golovko, A. B. Danilov [26]. Fluctuations of indicators in this case can be explained by differences in the elemental composition of the investigated coal [27].…”

Section: Discussionsupporting

confidence: 92%

Dependence of the Yield of Chemical Coking Products from Coal Concentrates on Their Nature

Васильева¹,

Cherkasova²,

Subbotin³

et al. 2016

Proceedings of the 8th Russian-Chinese Symposium "Coal in the 21st Century: Mining, Processing, Safety"

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-The relevance of the work is justified by the need for a comprehensive assessment of the quality of coal concentrate used to produce coal blends in the coking process, and resources of coking chemical products derived from them. This information is necessary for making optimal coal blends for coking and for planning of coking plants operation. The purpose of work is to study the impact of the qualitative characteristics of the Kuznetsk Basin coal concentrates on the yield and composition of coking chemical products for the purpose of making coal blends for coking on their basis. In the course of studies, the following indicators have been identified: the technical analysis, caking, petrographic analysis, the yield of chemical coking products from coal concentrates and strength of the resulting coke residue. The main results of the study are the data on the main indicators of the quality of the investigated coals of the Kuznetsk basin and the coking yield as well as the relationships between these parameters. The results will later be used in the preparation of optimal coal blends for coking in the real production conditions of OAO "Koks".

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Section: Discussionsupporting

confidence: 92%

Dependence of the Yield of Chemical Coking Products from Coal Concentrates on Their Nature

Васильева¹,

Cherkasova²,

Subbotin³

et al. 2016

Proceedings of the 8th Russian-Chinese Symposium "Coal in the 21st Century: Mining, Processing, Safety"

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“…By-product yield is a fundamental factor in planning and evaluation of the operation of byproduct coking enterprises, therefore, the issue of forecasting this parameter is fundamental in planning cost-performance ratio of production. Since the 1920s, a large number of dependences of the yield of various by-products on the coal quality coefficient, from the volatile-matter yield to methods based on a modern understanding of their structure and properties, determined on the basis of data obtained during petrographic and ultimate analyzes [2][3][4], including with the calculation of the chemical potential of coal [5,6].…”

Section: Introductionmentioning

confidence: 99%

Development and Performance Evaluation of a Computer Program Based on Neural Network Mathematical Models for Forecasting By- Product Yield

2020

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Process performance of coking plants are based on data on the yield of by-products of coking coal and their quality, therefore, much attention is paid to the issues of their analysis. In view of the complexity and insufficient knowledge of the relationship between these parameters, mathematical modeling of this dependence using neural networks is of great interest. Based on a mathematical analysis of experimental data on the quality indicators of coal, coal concentrates and the by-product yield, neural network mathematical models have been developed to forecast the parameters under study. The neural network is based on the Ward’s network. Based on the results of the research, the application “Intelligent Information System for Forecasting By-product Yield” was created, which implements neural networks [1]. The relative forecasting error for the parameter “coke” is 0.64±0.23%, “coal tar” is 19.53±5.25%, “crude benzene” is 10.02±2.83%, and “coke gas” is 5.11±1.34%. A comparative analysis of the data obtained using the developed design method is carried out, with the simulation results using existing methods, as well as with the production values of by-products yield.

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Electromagnetic Radiation Absorption Polymer Ceramic-Inorganic Composites Mechanical Properties Optimization

Lebedev,

Shestopalov,

Vyrovets

et al. 2023

Lecture Notes in Networks and Systems

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Predicting the yield of coke-plant products on the basis of petrographic analysis

Cited by 11 publications

References 0 publications

Dependence of the Yield of Chemical Coking Products from Coal Concentrates on Their Nature

Dependence of the Yield of Chemical Coking Products from Coal Concentrates on Their Nature

Development and Performance Evaluation of a Computer Program Based on Neural Network Mathematical Models for Forecasting By- Product Yield

Electromagnetic Radiation Absorption Polymer Ceramic-Inorganic Composites Mechanical Properties Optimization

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