4.5 Article

Advances in wood drying research and development

Journal

DRYING TECHNOLOGY
Volume 41, Issue 6, Pages 890-914

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/07373937.2023.2205530

Keywords

Wood drying; moisture movement; drying stress; wood collapse; drying schedule; novel-drying technologies

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This paper provides a review of research and development in wood drying, focusing on the understanding of the drying process, mechanisms of drying defect occurrence, and affecting factors. Recent progress in understanding drying stress development and wood collapse formation are presented, along with improvements in drying schedule and novel drying technologies. The application of artificial intelligence for modeling and control of timber drying is also briefly discussed. Recommendations for future studies and practical implementation are provided.
Wood drying is a key operation of wood processing to ensure that the wood retains its physical integrity and stability in remanufacturing and in use. However, in industrial drying various drying defects still occur, which include uneven moisture content between and within boards, board distortion, residual drying stresses that may induce internal and external checking, and wood collapse. This paper presents a review on advances in wood drying research and development, which lay foundation for better understanding of the drying process, mechanisms of drying defect occurrence and affecting factors. In particular, recent progresses in understanding drying stress development and wood collapse formation during drying are presented in more details. Based on these advances, inter-linkage and interactions are analyzed among wood physical and microstructural properties, moisture movement in wood during drying, stress development and reversal, and wood collapse formation. Following this, drying schedule improvements and novel drying technologies are presented with targets to mitigate the drying defects, reduce energy consumption and increase the productivity. Application of artificial intelligence for modeling and control of the timber drying is also briefly described. Finally, recommendations are made for future studies and practical implementation.

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