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| Main Authors: | , , , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2020
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| Subjects: | |
| Online Access: | https://doi.org/10.3390/ma13071699 |
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Table of Contents:
- <p>The novelty of this study is the development of an accurate wood moisture content (MC)<br>estimation method based on a relatively brand-new, non-destructive testing technique (drilling chips<br>extraction). The method is especially important in the assessment of existing timber structures,<br>where non-destructive testing (NDT) results are a ected by wood MC and should be adjusted to a<br>reference MC, usually 12%. In the assessment of timber structures, it is not possible to determine MC<br>by oven drying method and this should be estimated. Electrical resistance and capacitance are the<br>conventional methods used for MC estimation. This research work aims to present an accurate MC<br>estimation method based on the drilling chips extraction technique. For that, 99 specimens (90 65 <br>38 mm3) from three softwood and hardwood species covering a wide range of densities (from 355 to<br>978 kg m 3) were tested after conditioning at five di erent MCs (5%, 10%, 15%, 20%, 25%). TheWood<br>Extractor device based on the drilling chips extraction technique was used. The mass of the chips<br>collected (drilling residue) from each drill was recorded. The results show that the MC of the chips<br>extracted was statistically significantly di erent than the MC of the specimen and cannot be directly<br>used as MC determination. However, the chips MC can be used as an estimator of specimen MC with<br>high determination coecients (R2 from 71% to 86%). As the main result, models to estimate density<br>directly adjusted to a reference 12% MC from the wet and dry mass of chips extracted were developed<br>with an R2 of 98%. In sum, the drilling chips extractor is a dependable and straightforward method<br>to estimate MC and density from only one measurement. Density adjusted to a reference 12% MC<br>can be directly estimated from a single model.</p>