Wood shrinkage in CT-scanning analysis

• Main Author: Couceiro, José
• Format: Others
• Language: English
• Published: Luleå tekniska universitet, Träteknik 2016
• Subjects: Bio Materials; Biomaterial
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-129; http://nbn-resolving.de/urn:isbn:978-91-7583-682-9; http://nbn-resolving.de/urn:isbn:978-91-7583-683-6

Computed tomography (CT) can be used to study wood-water interactions in differentways, such as by determining wood moisture content (MC). The determination of MCrequires two CT images: one at the unknown moisture distribution and a second one ata known reference MC level, usually oven-dry MC. The two scans are then compared.If the goal is to determine the MC in local regions, when studying moisture gradients forinstance, wood shrinkage must be taken into account during the data processing of theimages. The anisotropy of wood shrinkage creates an obstacle, however, since theshrinkage is not uniform throughout the wood specimen. The objective of this thesis was to determine the shrinkage in wood in each pixel of aCT image. The work explores two different methods that estimate from CT images, thelocal shrinkage of a wood specimen between two different MC levels. The first methoddetermines shrinkage for each pixel using digital image correlation (DIC) and isembedded in a wider method to estimate the MC, which is the parameter verifiedagainst a reference. It involves several steps in different pieces of software, making ittime-consuming and creating many sources of possible experimental errors. The MCdetermined by this method showed a strong correlation with the gravimetricallymeasured MC, showing an R2 of 0.93 and the linear regression model predicted MCwith a RMSE of 1.4 MC percentage points. The second method uses the displacement information generated from the spatialalignment of the CT images in order to compute wood shrinkage in the radial andtangential directions. All the required steps are combined into a single computeralgorithm, which reduces the sources of error and facilitates the process. The RMSEbetween this method and the determination of shrinkage measured in the CT imagesusing CAD has shown acceptable small differences. Both methods have proved to be useful tools to deal with shrinkage in different ways byusing CT images. In one case MC was successfully estimated, being the shrinkagecalculation a necessary step in the process, and in the other case the radial and tangentialshrinkages were successfully estimated for each pixel. Nevertheless, the difficulty incomparing the shrinkage coefficient calculated for local regions with a reference valuesuggest that more research must be carried out in order to be able to draw reliableconclusions.