Moisture content prediction of rain-exposed wood: Test and evaluation of a simple numerical model for durability applications

Abstract

Decay prediction models are frequently used to estimate the service life of wooden components. These models require knowledge of how the material climate, i.e. moisture content and material temperature, varies over time. Therefore, a reliable material climate prediction model is crucial in situations when measurements are not viable. The aim of this paper is to test and evaluate the performance of a simple numerical moisture transport model for rain-exposed wood. The main focus is on the influence of rain and moisture transport in the transversal direction. First, a model based on Fick's second law of diffusion was calibrated against laboratory measurements where wooden boards were exposed to artificial rain. Second, the model was tested against field-test measurements on wooden boards in use-class 3.1, i.e. above-ground, exposed to rain and free to dry. The influence of rain was investigated by studying the difference between sheltered and exposed specimens over time. Finally, the model was applied to a number of Swedish climates and two different decay-prediction models were used to assess the output.The main conclusion is that the influence of rain can be reproduced with sufficient accuracy for the particular application. The error between the numerical result and measurements tends to increase with decreasing temperature and at high moisture contents. However, the total error is reduced when the moisture content history is post-processed in a decay-prediction model as the rate of decay tends to decrease with decreasing temperature.

The effects of joints on the moisture behaviour of rain exposed wood: a numerical study with experimental validation

“…The data on precipitation was measured in volume per unit of time while the model is designed with duration of exposure as input. The following equation was used to convert the data from volume per hour to duration (Niklewski et al 2016):…”

“…The maximum time-step was set to 0.05 h, which was necessary in order to prevent the solver from bypassing spray sequences of short durations. A more detailed description of the implementation into the software is given by Niklewski et al (2016).…”

“…In addition, the smaller rain-induced fluctuations could be related to the material in question having lower permeability than plain sapwood, as neither heartwood-content nor density was documented. A more detailed analysis on the free horizontal board, including sources of error, model accuracy and surface conditions can be found in Niklewski et al (2016). Qualitatively, the model captured the increased difference between the horizontal board and the two joints during periods with high amounts of precipitation.…”

“…Moisture transport can be described with the moisture gradient as the driving potential, a diffusion coefficient that governs the rate of transport in the material and a mass transfer coefficient that governs the interaction with the air. This type of model has predominantly been used for modelling moisture transfer in the hygroscopic moisture range but has also been used to model free water flux (see Derbyshire and Robson 1999;De Meijer and Militz 2000;Virta et al 2006;Niklewski et al 2016). Liquid moisture transport is driven by capillary pressure differentials ; however, it is frequently described by the moisture gradient as the driving potential by utilizing the relationship between capillary pressure and degree of saturation (Spolek and Plumb 1981).…”

“…In the present study, the moisture distribution in a specific type of joint was studied through the use of a numerical model based on Fick's second law of diffusion. The study builds on a previous publication (Niklewski et al 2016), where a one-dimensional model for transverse moisture transport in panels was proposed. In the present study, the focus was instead on the moisture behaviour of joints.…”