Abstract
In CFB combustion, fuel conversion is limited by mass and
heat transfer and chemical reactions inside the particle.
In CFD simulation, computation of the local instantaneous
conversion rate of a single fuel particle should be fast.
The objective of the present study is to convert a
shrinking particle model for coal combustion into a
correlation based description that can easily be
implemented in a CFD code. The single particle model was
used to produce net reaction rates averaged over particle
volume in a wide range of fluidization, temperature and
composition conditions. The data was used to train neural
network models that are fast to compute and easy to
implement in a CFD code.
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Publisher | Częstochowa University of Technology (CUT) |
| Pages | 765-772 |
| ISBN (Print) | 978-83-62079-16-2 |
| Publication status | Published - 1 Jan 2017 |
| MoE publication type | A4 Article in a conference publication |
| Event | 12th International Conference on Fluidized Bed Technology, CFB-12 - Krakow, Poland Duration: 23 May 2017 → 26 May 2017 |
Conference
| Conference | 12th International Conference on Fluidized Bed Technology, CFB-12 |
|---|---|
| Abbreviated title | CFB-12 |
| Country/Territory | Poland |
| City | Krakow |
| Period | 23/05/17 → 26/05/17 |
Keywords
- char
- combustion
- gasification
- modeling
- neural network
- shrinking particle