### Abstract

In CFD simulation of CFB combustion, computation of the
local instantaneous conversion rate of a single fuel
particle should be fast. Since fuel conversion is limited
by mass and heat transfer and the rates of chemical
reactions inside the particle, the optimal model would
produce the internal conditions as a function of
location. As rigorous 1D, 2D and 3D fuel conversion
models presented in the literature are often too
time-consuming for CFD environment, simplified 0D
approaches have been suggested. To reduce the amount of
simplification, the present study introduces an
alternative approach that converts a rigorous fuel
conversion model into correlations that can be
implemented in a CFD code. As a demonstration example, a
1D shrinking particle model for coal combustion is
converted into a correlation based description. The
single particle model is used to produce a data set of
net reaction rates averaged over particle volume in a
wide range of fluidization, temperature and composition
conditions. The data is then used to train neural network
models that are fast to compute and easy to implement in
a CFD code.

Original language | English |
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Pages (from-to) | 236-243 |

Number of pages | 8 |

Journal | Fuel Processing Technology |

Volume | 169 |

DOIs | |

Publication status | Published - 2018 |

MoE publication type | A1 Journal article-refereed |