Modelling coal gasification with a hybrid neural network

Bing Guo, Youting Shen, Dingkai Li, Fu Zhao

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

Gasification of two coals was carried out in a batch feed fluidized bed reactor at atmospheric pressure using steam as fluidizing medium. A model of coal gasification was developed, incorporating a first-principles model with a neural network parameter estimator. The hybrid neural network was trained with experimental data for the two coals and gave good performance in process modelling. A parameter for the overall reactivity of char, namely 'active char ratio' (ACR), was identified by the neural network, as a function of gasification time and temperature. The ACR profile showed a strong dependence on coal type. Other parameters estimated by the neural network also reflected distinct characteristics of the two coals.

Original languageEnglish
Pages (from-to)1159-1164
Number of pages6
JournalFuel
Volume76
Issue number12
Publication statusPublished - Oct 1997
Externally publishedYes

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Keywords

  • Coal gasification
  • Mathematical modelling
  • Neural networks

ASJC Scopus subject areas

  • Organic Chemistry
  • Energy Engineering and Power Technology
  • Fuel Technology

Cite this

Guo, B., Shen, Y., Li, D., & Zhao, F. (1997). Modelling coal gasification with a hybrid neural network. Fuel, 76(12), 1159-1164.