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Porosity estimation of Phyllostachys edulis (Moso bamboo) by computed tomography and backscattered electron imaging

Huang, Puxi, Chang, Wen-Shao, Ansell, Martin P., Chew, Y. M. John and Andy, Shea 2017. Porosity estimation of Phyllostachys edulis (Moso bamboo) by computed tomography and backscattered electron imaging. Wood Science and Technology 51 (1) , pp. 11-27. 10.1007/s00226-016-0865-6

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Abstract

This study aims to investigate and quantify the porosity in the cross section of Phyllostachys edulis (Moso bamboo) culm wall. The porosity results are expected to be utilised in numerical study of heat and moisture transfer. Computed tomography (CT) and backscattered electron (BSE) imaging methods are utilised in this study because these two methods allow measurements of the anisotropic features of bamboo specimens. The results of these two methods can be represented as the function of the real dimension rather than the pore size distribution of the specimen. The specimens are obtained from eight different locations along the Moso bamboo culms. Both internodes and nodes specimens are measured in this study. The average porosity, standard deviation (SD) and coefficient of variation (COV) are calculated for BSE and CT results. Pearson product-moment correlation coefficient (PPMCC) is also calculated in this study to analyse the correlation between the BSE results and CT results. Typical porosity results from 400 sampling points and 10 portions average porosity are analysed in this study. The CT scanning results show similar trend with BSE results. The correlation relationship between BSE and CT results approaches moderate correlation level to strong correlation level. The average porosity of internode specimens is from 43.9 to 58.8 % by BSE measurement and from 44.9 to 63.4 % by CT measurement. The average porosity of node specimens is from 37.4 to 56.6 % by BSE measurement and from 32.1 to 62.2 % by CT measurement.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Architecture
Publisher: Springer
ISSN: 0043-7719
Date of First Compliant Deposit: 1 December 2017
Last Modified: 12 Jul 2019 12:48
URI: http://orca.cf.ac.uk/id/eprint/107197

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