Wood chips flow in a rotary kiln: experiments and modeling - IMT Mines Albi-Carmaux Accéder directement au contenu
Article Dans Une Revue Chemical Engineering Research and Design Année : 2015

Wood chips flow in a rotary kiln: experiments and modeling

Résumé

Rotary kilns are well suited for processing woody biomass by torrefaction to produce bioenergy. One of the key issues for process design lies in the flow pattern modeling. The Saeman model is classically used to predict the mean residence time (MRT) and the bed depth profile of powder materials in rotary kilns. Its ability to describe wood chips flow arises. In the present study, residence time distribution (RTD) experiments are conducted with raw and torrefied wood chips. Effects of operating parameters – kiln slope, rotational speed and inlet flow-rate – on the average residence time, the variance and the mean solid hold-up are discussed. A plug flow with small extent of dispersion is emphasized, even if some segregation phenomena are highlighted. Torrefaction did not evidence any significant influence on the flow pattern. With a discrepancy of 20 % between the measured and computed mean residence time, the predictive capacity of the classical Seaman model proved to be insufficient. The model is adapted to predict accurately the load profile and the mean residence time of particles with parallelepiped form. The discrepancy between experimental and calculated results is so reduced from 20 to 5 % for the MRT and from 25 to 5 % for the mean solid hold-up.
Fichier principal
Vignette du fichier
Paper_HAL.pdf (917.12 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01165159 , version 1 (18-06-2015)

Identifiants

Citer

Baptiste Colin, Jean-Louis Dirion, Patricia Arlabosse, Sylvain Salvador. Wood chips flow in a rotary kiln: experiments and modeling. Chemical Engineering Research and Design, 2015, 98, pp.179-187. ⟨10.1016/j.cherd.2015.04.017⟩. ⟨hal-01165159⟩
155 Consultations
1155 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More