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A relevant and robust vacuum-drying model applied to hardwoods

Authors :
Elliot J. Carr
Patrick Perré
Adam L. Redman
Ian Turner
Henri Bailleres
Queensland University of Technology [Brisbane] (QUT)
Queensland Department of Primary Industries and Fisheries
Emerging Technologies
Laboratoire de Génie des Procédés et Matériaux - EA 4038 (LGPM)
CentraleSupélec
Source :
Wood Science and Technology, Wood Science and Technology, Springer Verlag, 2017, 51 (4), pp.701-719. ⟨10.1007/s00226-017-0908-7⟩
Publication Year :
2017
Publisher :
HAL CCSD, 2017.

Abstract

International audience; A robust mathematical model was developed to simulate the heat and mass transfer process that evolves during vacuum-drying of four commercially important Australian native hardwood species. The hardwood species investigated were spotted gum (Corymbia citriodora), blackbutt (Eucalyptus pilularis), jarrah (Eucalyptus marginata), and messmate (Eucalyptus obliqua). These species provide a good test for the model based on their extreme diversity between wood properties and drying characteristics. The model uses boundary condition data from a series of vacuum-drying trials, which were also used to validate predictions. By using measured diffusion coefficient values to calibrate empirical formula, the accuracy of the model was greatly improved. Results of a sensitivity analysis showed that the model outputs provide excellent agreement with experimental observation despite the large range of species behaviour and variation in wood properties. This study confirms that the drying rate is significantly improved as a direct result of the enhanced convective and diffusive transfer along the board thickness. Contrary to softwood, it appears that longitudinal migration provides only a secondary effect. Not only is the model able to predict the heat and mass transfer behaviour of a range of hardwood species, it is also flexible enough to predict the behaviour for both conventional and vacuum-drying scenarios. The outcomes of this work provide the hardwood industry with a well-calibrated predictive drying tool that can be used to optimise drying schedules.

Details

Language :
English
ISSN :
00437719 and 14325225
Database :
OpenAIRE
Journal :
Wood Science and Technology, Wood Science and Technology, Springer Verlag, 2017, 51 (4), pp.701-719. ⟨10.1007/s00226-017-0908-7⟩
Accession number :
edsair.doi.dedup.....310d2cc70aa341c8cc4fef29e5a35cae
Full Text :
https://doi.org/10.1007/s00226-017-0908-7⟩