Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models

Two detailed pyrolysis models are used to predict pyrolysis products of the conversion of two biomass fuels in a drop tube reactor. In both models, biomass is considered as a combination of the reference components cellulose, hemicellulose and lignin, but their mathematical modelling approaches are...

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Main Authors: M. Rabacal, M. Costa, M. Vascellari, C. Hasse
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2014-06-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/5708
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author M. Rabacal
M. Costa
M. Vascellari
C. Hasse
author_facet M. Rabacal
M. Costa
M. Vascellari
C. Hasse
author_sort M. Rabacal
collection DOAJ
description Two detailed pyrolysis models are used to predict pyrolysis products of the conversion of two biomass fuels in a drop tube reactor. In both models, biomass is considered as a combination of the reference components cellulose, hemicellulose and lignin, but their mathematical modelling approaches are different. Two distinct methods are used to estimate the composition of the biomass fuels based on their ultimate and proximate analysis. A heat balance is applied to the particle, considering convective and radiative heat transfer along with drying effects. A tar cracking model was used in a post-processing step. The results obtained using different combinations of pyrolysis models and methods to estimate the composition were compared to experimental results. All combinations used under-estimated the total volatile yield, and the tar cracking model is necessary to capture the final yields of gas and tar. Finally, the predicted pyrolysis products very sensitive to the composition of the biomass.
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spelling doaj.art-3e34baf45bf044bb806a6525279ee7bb2022-12-21T23:47:22ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162014-06-013710.3303/CET1437014Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive ModelsM. RabacalM. CostaM. VascellariC. HasseTwo detailed pyrolysis models are used to predict pyrolysis products of the conversion of two biomass fuels in a drop tube reactor. In both models, biomass is considered as a combination of the reference components cellulose, hemicellulose and lignin, but their mathematical modelling approaches are different. Two distinct methods are used to estimate the composition of the biomass fuels based on their ultimate and proximate analysis. A heat balance is applied to the particle, considering convective and radiative heat transfer along with drying effects. A tar cracking model was used in a post-processing step. The results obtained using different combinations of pyrolysis models and methods to estimate the composition were compared to experimental results. All combinations used under-estimated the total volatile yield, and the tar cracking model is necessary to capture the final yields of gas and tar. Finally, the predicted pyrolysis products very sensitive to the composition of the biomass.https://www.cetjournal.it/index.php/cet/article/view/5708
spellingShingle M. Rabacal
M. Costa
M. Vascellari
C. Hasse
Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models
Chemical Engineering Transactions
title Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models
title_full Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models
title_fullStr Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models
title_full_unstemmed Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models
title_short Kinetic Modelling of Sawdust and Beech Wood Pyrolysis in Drop Tube Reactors Using Advanced Predictive Models
title_sort kinetic modelling of sawdust and beech wood pyrolysis in drop tube reactors using advanced predictive models
url https://www.cetjournal.it/index.php/cet/article/view/5708
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AT mcosta kineticmodellingofsawdustandbeechwoodpyrolysisindroptubereactorsusingadvancedpredictivemodels
AT mvascellari kineticmodellingofsawdustandbeechwoodpyrolysisindroptubereactorsusingadvancedpredictivemodels
AT chasse kineticmodellingofsawdustandbeechwoodpyrolysisindroptubereactorsusingadvancedpredictivemodels