A method to estimate wood surface moisture content during drying
A method to estimate the surface moisture content below the fibre saturation point that is a function of the surface temperature, wet- and dry bulb temperatures, equilibrium moisture content, and fibre saturation point was evaluated. The method is based on the premise that the surface temperature is...
Guardado en:
Autores principales: | , , |
---|---|
Lenguaje: | English |
Publicado: |
Universidad del Bío-Bío
2017
|
Materias: | |
Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2017000200001 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:scielo:S0718-221X2017000200001 |
---|---|
record_format |
dspace |
spelling |
oai:scielo:S0718-221X20170002000012017-05-02A method to estimate wood surface moisture content during dryingScheepers,GWiberg,PJohansson,J Dry bulb temperature equilibrium moisture content fibre saturation point moisture measurement surface temperature wet bulb temperature A method to estimate the surface moisture content below the fibre saturation point that is a function of the surface temperature, wet- and dry bulb temperatures, equilibrium moisture content, and fibre saturation point was evaluated. The method is based on the premise that the surface temperature is solely influenced by the surface moisture content and the climate that the surface is exposed to. The prediction model contends that the surface moisture content is equal to the fibre saturation point when the surface temperature is equal to the wet bulb temperature, and equal to the equilibrium moisture content when the surface temperature is equal to the dry bulb temperature, with a linear interpolation between those two points. The model thus predicts that the average moisture content of a thin piece of veneer can be predicted with fairly good accuracy. Also, when drying boards in a fast changing climate, e.g. fan reversals in industrial kilns, the surface temperature and surface moisture content should change as abruptly as the climate does. Additionally, the surface moisture content should correlate to the known drying phases, with a consistently high surface moisture content during the capillary phase when the wet line is close to the surface, and a quickly decreasing surface moisture content when the wet line moves into the wood during the transition to the diffusion phase. The prediction model was tested in these three scenarios and the results suggest that the basic premise is reasonable, and that the method is useful for surface moisture content estimation.info:eu-repo/semantics/openAccessUniversidad del Bío-BíoMaderas. Ciencia y tecnología v.19 n.2 20172017-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2017000200001en10.4067/S0718-221X2017005000011 |
institution |
Scielo Chile |
collection |
Scielo Chile |
language |
English |
topic |
Dry bulb temperature equilibrium moisture content fibre saturation point moisture measurement surface temperature wet bulb temperature |
spellingShingle |
Dry bulb temperature equilibrium moisture content fibre saturation point moisture measurement surface temperature wet bulb temperature Scheepers,G Wiberg,P Johansson,J A method to estimate wood surface moisture content during drying |
description |
A method to estimate the surface moisture content below the fibre saturation point that is a function of the surface temperature, wet- and dry bulb temperatures, equilibrium moisture content, and fibre saturation point was evaluated. The method is based on the premise that the surface temperature is solely influenced by the surface moisture content and the climate that the surface is exposed to. The prediction model contends that the surface moisture content is equal to the fibre saturation point when the surface temperature is equal to the wet bulb temperature, and equal to the equilibrium moisture content when the surface temperature is equal to the dry bulb temperature, with a linear interpolation between those two points. The model thus predicts that the average moisture content of a thin piece of veneer can be predicted with fairly good accuracy. Also, when drying boards in a fast changing climate, e.g. fan reversals in industrial kilns, the surface temperature and surface moisture content should change as abruptly as the climate does. Additionally, the surface moisture content should correlate to the known drying phases, with a consistently high surface moisture content during the capillary phase when the wet line is close to the surface, and a quickly decreasing surface moisture content when the wet line moves into the wood during the transition to the diffusion phase. The prediction model was tested in these three scenarios and the results suggest that the basic premise is reasonable, and that the method is useful for surface moisture content estimation. |
author |
Scheepers,G Wiberg,P Johansson,J |
author_facet |
Scheepers,G Wiberg,P Johansson,J |
author_sort |
Scheepers,G |
title |
A method to estimate wood surface moisture content during drying |
title_short |
A method to estimate wood surface moisture content during drying |
title_full |
A method to estimate wood surface moisture content during drying |
title_fullStr |
A method to estimate wood surface moisture content during drying |
title_full_unstemmed |
A method to estimate wood surface moisture content during drying |
title_sort |
method to estimate wood surface moisture content during drying |
publisher |
Universidad del Bío-Bío |
publishDate |
2017 |
url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2017000200001 |
work_keys_str_mv |
AT scheepersg amethodtoestimatewoodsurfacemoisturecontentduringdrying AT wibergp amethodtoestimatewoodsurfacemoisturecontentduringdrying AT johanssonj amethodtoestimatewoodsurfacemoisturecontentduringdrying AT scheepersg methodtoestimatewoodsurfacemoisturecontentduringdrying AT wibergp methodtoestimatewoodsurfacemoisturecontentduringdrying AT johanssonj methodtoestimatewoodsurfacemoisturecontentduringdrying |
_version_ |
1714202635767119872 |