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Software for Efficient Chemical Technologies for Processing of Apatite–Nepheline Ore Waste

Authors
  • Meshalkin, V. P.1, 2
  • Dli, M. I.3
  • Puchkov, A. Yu.3
  • Bobkov, V. I.3
  • Kazak, A. S.4
  • 1 Mendeleev University of Chemical Technology of Russia, Moscow, 127047, Russia , Moscow (Russia)
  • 2 Kurnakov Institute of General and Inorganic Chemistry, Russian Academy of Sciences, Moscow, 119991, Russia , Moscow (Russia)
  • 3 Branch of National Research University “Moscow Power Engineering Institute”, Smolensk, 214013, Russia , Smolensk (Russia)
  • 4 OOO Research Institute of Economy and Management in the Gas Industry, Moscow, 119311, Russia , Moscow (Russia)
Type
Published Article
Journal
Doklady Chemistry
Publisher
Pleiades Publishing
Publication Date
Feb 01, 2021
Volume
496
Issue
2
Pages
42–47
Identifiers
DOI: 10.1134/S0012500821020014
Source
Springer Nature
Keywords
License
Yellow

Abstract

AbstractAspects of the methodological support of digital twins were presented by the example of the chemical and energy engineering process of phosphorus production from apatite–nepheline ore waste. Algorithmic support was developed for one of the levels of the hierarchy of the information structure of a self-refining digital twin. This support is intended for the complex optimization of the operation of the phosphorus production plant according to the criterion of the minimum resource consumption. The algorithm is based on the ensemble application of deep neural networks, the training of which can continue during the operation of the plant. The results of a model experiment performed using the created program that implemented the developed algorithmic support of the self-refining digital twin were presented.

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