### Abstract

Original language | English |
---|---|

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 |

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**Modeling of conversion of a single fuel particle in a CFD model for CFB combustion.** / Niemi, Timo; Kallio, Sirpa.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Modeling of conversion of a single fuel particle in a CFD model for CFB combustion

AU - Niemi, Timo

AU - Kallio, Sirpa

N1 - Project code: 114304

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85042162685&partnerID=8YFLogxK

U2 - 10.1016/j.fuproc.2017.10.010

DO - 10.1016/j.fuproc.2017.10.010

M3 - Article

VL - 169

SP - 236

EP - 243

JO - Fuel Processing Technology

JF - Fuel Processing Technology

SN - 0378-3820

ER -