Modelling coal gasification with a hybrid neural network Academic Article uri icon

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. © 1997 Elsevier Science Ltd.

author list (cited authors)

  • Guo, B., Shen, Y., Li, D., & Zhao, F. u.

citation count

  • 26

publication date

  • October 1997

published in