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Identifying Efficient Transport Pathways in Early-Wood Timber: Insights from 3D X-ray CT Imaging of Softwood in the Presence of Flow.

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Title: Identifying Efficient Transport Pathways in Early-Wood Timber: Insights from 3D X-ray CT Imaging of Softwood in the Presence of Flow.
Authors: Burridge, H. C.1 (AUTHOR), Pini, R.2 (AUTHOR) r.pini@imperial.ac.uk, Shah, S. M. K.2,3 (AUTHOR), Reynolds, T. P. S.4 (AUTHOR), Wu, G.5 (AUTHOR), Shah, D. U.6 (AUTHOR), Scherman, O. A.5 (AUTHOR), Ramage, M. H.6 (AUTHOR), Linden, P. F.7 (AUTHOR)
Source: Transport in Porous Media. 2021, Vol. 136 Issue 3, p813-830. 18p.
Subjects: Mechanical behavior of materials, X-ray imaging, Computed tomography, Fluid flow, Softwood
Abstract: Wider use of timber has the potential to greatly reduce the embodied carbon of construction. Improved chemical treatment could help overcome some of the barriers to wider application of timber, by furthering the durability and/or mechanical properties of this natural material. Improving timber treatment by treating the whole volume of a piece of timber, or tailored sections thereof, requires sound understanding and validated modelling of the natural paths for fluid flow through wood. In this study we carry out a robust analysis of three-dimensional X-ray CT measurements on kiln-dried softwood in the presence of flow and identify small portions of early-wood which are uniquely capable of transporting fluids—herein 'efficient transport pathways'. We successfully model the effects of these pathways on the liquid uptake by timber by introducing a spatial variability in the amount of aspiration of the bordered pits following kiln drying. The model demonstrates that fluid advances along these efficient transport paths between 10 and 30 times faster than in the remainder of the timber. Identifying these efficient transport pathways offers scope to improve and extend the degree to which timber properties are enhanced at an industrial scale through processes to impregnate timber. [ABSTRACT FROM AUTHOR]
Copyright of Transport in Porous Media is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Wider use of timber has the potential to greatly reduce the embodied carbon of construction. Improved chemical treatment could help overcome some of the barriers to wider application of timber, by furthering the durability and/or mechanical properties of this natural material. Improving timber treatment by treating the whole volume of a piece of timber, or tailored sections thereof, requires sound understanding and validated modelling of the natural paths for fluid flow through wood. In this study we carry out a robust analysis of three-dimensional X-ray CT measurements on kiln-dried softwood in the presence of flow and identify small portions of early-wood which are uniquely capable of transporting fluids—herein 'efficient transport pathways'. We successfully model the effects of these pathways on the liquid uptake by timber by introducing a spatial variability in the amount of aspiration of the bordered pits following kiln drying. The model demonstrates that fluid advances along these efficient transport paths between 10 and 30 times faster than in the remainder of the timber. Identifying these efficient transport pathways offers scope to improve and extend the degree to which timber properties are enhanced at an industrial scale through processes to impregnate timber. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Transport in Porous Media is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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