Calibration and comparison of two moisture content measurement methods for in situ monitoring of beech laminated veneer lumber

Abstract

A timber bridge constructed in 1815 was renovated in 2018, wherein the load-bearing system was reinforced with beech laminated veneer lumber (LVL) elements. Beech LVL is primarily found in dry and heated structures (Service Class 1). Although the material of this bridge would not be directly exposed to weather, it would be exposed to outdoor relative humidity ranging between 50% in spring and 90% or higher in autumn (Service Class 2). Thus, the moisture content development in the reinforcements was monitored to observe the response of the material under such conditions. The moisture content was measured using both sorptive and electrical resistance methods. The relationship between the electrical resistance of the material to moisture content and sorption isotherms was determined through laboratory experiments. Thereafter, the derived relationships were used to determine the moisture content measured on the bridge over a period of two years. Consequently, the two measurement methods resulted in overlapping of moisture content values, which remained within safe levels and are expected to be maintained in future. The overlapping moisture content measurements validated that either of the monitoring methods could be independently deployed to obtain reliable results.

Calibration of Electrical Resistance to Moisture Content for Beech Laminated Veneer Lumber “BauBuche S” and “BauBuche Q”

“…Therefore, it cannot be suggested with certainty that a different calibration for the two different measurement depths will be necessary for all BB-Q panels in general. However, the three calibrations of "BauBuche" in this study are close to one another in relation to solid beech, and they display a nearly perfect agreement with data from Schiere et al [23] obtained with different types of electrodes and different panels. Due to the assumption on temperature correction, the range of application should be limited to heated indoor conditions where the MC does not vary in an extreme manner.…”

“…Therefore, if not for the simplicity of a two-parameter model, the authors recommend using model B for the calibration of R to MC for "BauBuche". The three calibrations of this study appeared to agree very well to a calibration for "BauBuche S" from Schiere et al [23], as shown in Figure 4a, and the beech LVL calibrations indeed differed from a calibration for solid European beech wood [26].…”

“…This might also be the case for further engineered wood products such as LVL. For beech LVL, a data-based temperature-corrected calibration was made in Schiere et al [23]; however, the calibration is based on data points collected only at 10 • C and 20 • C. Furthermore, Figure 4b shows that a data-based temperature correction did not add an apparent benefit in terms of precision in the case of beech LVL. It can be seen that the corrections of BB-S using Equation ( 3…”

“…There is an increasing demand for MC-monitoring in timber structures where beech LVL is employed [20,21]. However, next to a report by Franke et al [22] and a recent study by Schiere et al [23] providing calibrations based on few data points, no other reliable calibration data sets exist for beech LVL. Furthermore, calibration curves for native beech wood cannot be used, since the wood's physical properties are altered during the LVL production process, often involving steps such as peeling, drying, heat and pressure treatment.…”

A Statistical Approach for Determining the Impact of Sensor Orientation and Electrode Type on Moisture Content Measurements in Eastern White Pine

“…This accumulation of moisture may lead to mould, mildew, health-related problems, and in extreme cases, cause wood components to rot, leading to structural failures. For lumber-based construction, these problems are caused by exposure of wood to high relative humidity levels over extended periods of time [1,2]. Several techniques exist today for measuring MC in wall assemblies, but these methods have high uncertainties when implemented during long-term field testing due to sensor drift and external sources of damage such as dust, rust, corrosion, etc.…”