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Applied Sciences
Article . 2021 . Peer-reviewed
License: CC BY
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Applied Sciences
Article
License: CC BY
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Applied Sciences
Article . 2021
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Drying Stress and Strain of Wood: A Review

Authors: Qin Yin; Hong-Hai Liu;

Drying Stress and Strain of Wood: A Review

Abstract

Wood drying stress causes various drying defects, which result from the wood microstructure and the transfer of heat and mass during the drying. It is the fundamental way to solve the problem of defects to clarify the law and mechanism of wood stress and strain development during drying. In this paper, based on the defects of wood drying, the theory and experimental testing methods of drying stress and strain were summarized. Meanwhile, artificial neural networks (ANN) and their application in the wood drying field were also investigated. The traditional prong and slicing methods were used practically in the research and industry of wood drying, but the stress changes in-process cannot be trapped. The technologies of image analysis and near-infrared spectroscopy provide a new opportunity for the detection of drying stress and strain. Hence, future interest should be attached to the combination of the theory of heat and mass transfer and their coupling during drying with the theory of microscopic cell wall mechanics and macroscopic drying. A more complete image acquisition and analysis system should be developed to realize the real-time monitoring of drying strain and cracking, practically. A more feasible and reasonable prediction model of wood drying stress and strain should be established to achieve the accuracy of the prediction.

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Keywords

Technology, QH301-705.5, T, Physics, QC1-999, drying stress, drying strain, Engineering (General). Civil engineering (General), back propagation network, Chemistry, detection methods, TA1-2040, Biology (General), QD1-999, artificial neural network

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    62
    popularity
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    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
62
Top 1%
Top 10%
Top 1%
gold