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Mathematical Problems in Engineering
Volume 2014, Article ID 506818, 8 pages
Research Article

Numerical Investigation of Characteristic of Anisotropic Thermal Conductivity of Natural Fiber Bundle with Numbered Lumens

Department of Building Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China

Received 6 July 2014; Accepted 15 July 2014; Published 6 August 2014

Academic Editor: Song Cen

Copyright © 2014 Guan-Yu Zheng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Natural fiber bundle like hemp fiber bundle usually includes many small lumens embedded in solid region; thus, it can present lower thermal conduction than that of conventional fibers. In the paper, characteristic of anisotropic transverse thermal conductivity of unidirectional natural hemp fiber bundle was numerically studied to determine the dependence of overall thermal property of the fiber bundle on that of the solid region phase. In order to efficiently predict its thermal property, the fiber bundle was embedded into an imaginary matrix to form a unit composite cell consisting of the matrix and the fiber bundle. Equally, another unit composite cell including an equivalent solid fiber was established to present the homogenization of the fiber bundle. Next, finite element thermal analysis implemented by ABAQUS was conducted in the two established composite cells by applying proper thermal boundary conditions along the boundary of unit cell, and influences of the solid region phase and the equivalent solid fiber on the composites were investigated, respectively. Subsequently, an optional relationship of thermal conductivities of the natural fiber bundle and the solid region was obtained by curve fitting technique. Finally, numerical results from the obtained fitted curves were compared with the analytic Hasselman-Johnson’s results and others to verify the present numerical model.