Open AccessMathematical model for predicting the formation of ferrous deposits during coal combustion
Author(s) -
M. Yu. Chernetskiy,
E. B. Butakov
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1677/1/012102
Subject(s) - ferrous , grinding , coal , combustion , coal combustion products , principal component analysis , artificial neural network , component (thermodynamics) , process engineering , environmental science , computer science , metallurgy , biological system , mineralogy , econometrics , materials science , waste management , chemistry , mathematics , engineering , thermodynamics , artificial intelligence , physics , organic chemistry , biology
For the first time, on the basis of a combined model of the principal component method and neural network modeling method, a unified method for evaluating coals for the formation of strong ferrous deposits is proposed, taking into account the ash composition, combustion conditions and the degree of grinding. The results of predicting the propensity to form ferrous deposits of Rfe have shown acceptable accuracy of determination. Expanding the experimental database on different types of coals will improve the accuracy of modeling and the widespread use of this technique in the energy sector.