Szczegóły publikacji
Opis bibliograficzny
Artificial intelligence treatment of $SO_{2}$ emissions from CFBC in air and oxygen-enriched conditions / J. Krzywański, W. NOWAK // Journal of Energy Engineering ; ISSN 0733-9402. — 2016 — vol. 142 iss. 1 art. no. 04015017, s. 04015017-1–04015017-10. — Bibliogr. s. 04015017-9–04015017-10
Autorzy (2)
- Krzywański Jarosław
- AGHNowak Wojciech Janusz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 97887 |
|---|---|
| Data dodania do BaDAP | 2016-05-24 |
| DOI | 10.1061/(ASCE)EY.1943-7897.0000280 |
| Rok publikacji | 2016 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Energy Engineering-ASCE |
Abstract
Because the complexity of sulfur capture and release during solid-fuel combustion in a circulating fluidized bed combustors (CFBC), especially in the oxygen-enriched combustion, has not been sufficiently recognized, the development of a simple model, which can correctly predict the SO2 emissions from such units over a wide range of operating conditions is of practical significance. The artificial neural network (ANN) approach is proposed in this paper, which may overcome the shortcomings of the experimental procedures and the programmed computing approach. The Ca:S molar ratio, oxygen concentration in inlet gas, excess oxygen, average riser temperature, mean diameter of the coal particles, average gas velocity in the riser, flue gas recycle ratio, and inlet gas pressure are taken into account by the model as the input parameters. The [8-3-7-1] ANN model with hyperbolic tangent sigmoid activation function was successfully applied to calculate the SO2 emissions from coal combustion in several CFB boilers operating under both air-fired and oxygen-enriched conditions.
