A computational study of a small-scale biomass burner: The influence of chemistry, turbulence and combustion sub-models. (1st July 2017)

• Record Type: Journal Article
• Authors: Farokhi, Mohammadreza; Birouk, Madjid; Tabet, Fouzi
• Is Part Of: Energy conversion and management. Volume 143(2017)
• Page Start: 203
• Page End: 217
• Publication Date: 2017-07-01
• Subjects: Biomass combustion -- Grate firing -- Steady flamelet model -- Unsteady flamelet model -- Eddy dissipation concept; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2017.03.086
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: The suitability of different combustion models for modeling biomass combustion was investigated. Temperature and major species were reasonably predicted by all tested combustion models. SFM was found incapable to reasonably predict slow-forming pollutants. UFM showed significant improvement of the prediction of CO concentration. The best prediction of CO concentration was achieved using the modified EDC model. Abstract: This paper presents a computational study to evaluate the influence of turbulence and combustion models as well as chemistry schemes on the combustion of a 8–11 kW small lab-scale biomass furnace. The analysis is conducted in the zone above the bed (freeboard) where the volatiles are burned. The turbulence models tested are standard k - ε, RNG k - ε and Realizable k - ε ; and the combustion models are SFM (Steady Flamelet Model), UFM (Unsteady Flamelet Model) and EDC (Eddy Dissipation Concept). In addition, several chemical mechanisms with different complexity (reduced and detailed chemical kinetics) are considered. The predictions of the velocity, species, and temperature fields are compared with their counterparts' experimental measurements. The present findings reveal that all tested combustion models (SFM, UFM and EDC) are capable of predicting temperature and major species profiles; whereas only EDC is able to reliably predict slow-chemistry species.