Prediction Distribution Model of Moisture Content in Laminated Wood Components

TL;DR

This paper develops a model to predict how moisture content changes over time and space in laminated wood components, helping prevent shrinkage cracks.

Contribution

A novel moisture field model for laminated wood is proposed, integrating heat and humidity transfer principles with finite element analysis.

Findings

The model accurately predicts equilibrium moisture content under various absorption and desorption conditions.

Moisture content reaches equilibrium faster with higher initial moisture gradients.

Component size and position significantly influence moisture distribution.

Abstract

Shrinkage cracks are some of the most common defects in timber structures obtained from woods with an uneven distribution of moisture content and are subject to external dynamic environmental changes. To accurately predict the changes in the moisture content of wood components at any time and position, this study first applied the principles of food drying and established a moisture field model for laminated wood based on the analogy between heat and humidity transfer. A model for predicting the moisture content of wood that considers time and spatial distribution was then proposed. Second, by collecting relevant experimental data and establishing a finite element analysis model, three moisture absorption conditions (0–9.95%, 0–13.65%, and 0–17.91%) and four desorption conditions (34–5.5%, 28–8.3%, 31–11.8%, and 25.5–15.9%) were analyzed. In the moisture absorption comparison, the time needed to reach 95% equilibrium moisture content was 2.43 days, 4.07 days, and 6.32 days. The rate at which the internal components reached equilibrium moisture content exceeded 10 days. The temporal and spatial distribution of wood moisture content revealed the correctness of the proposed wood moisture field model. Finally, the moisture content prediction model was applied in the order of characteristic equation solutions, moisture content gradient difference, and laminated wood size. The results revealed that the established humidity field model can predict the wood moisture content and how it changes over time and in space. Notably, 1–2 orders for the solution of the characteristic equation are recommended when applying the prediction model. The greater the difference in moisture content, the faster the equilibrium moisture content is reached. The moisture content varies greatly based on the component size and position. Notably, the influence of moisture gradient and wood size on the average wood moisture content cannot be ignored.

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