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      Estimation of the poroelastic parameters of cortical bone

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      Journal of Biomechanics
      Elsevier BV

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          Abstract

          Cortical bone has two systems of interconnected channels. The largest of these is the vascular porosity consisting of Haversian and Volkmann's canals, with a diameter of about 50 microm, which contains a.o. blood vessels and nerves. The smaller is the system consisting of the canaliculi and lacunae: the canaliculi are at the submicron level and house the protrusions of the osteocytes. When bone is differentially loaded, fluids within the solid matrix sustain a pressure gradient that drives a flow. It is generally assumed that the flow of extracellular fluid around osteocytes plays an important role not only in the nutrition of these cells, but also in the bone's mechanosensory system. The interaction between the deformation of the bone matrix and the flow of fluid can be modelled using Biot's theory of poroelasticity. However, due to the inhomogeneity of the bone matrix and the scale of the porosities, it is not possible to experimentally determine all the parameters that are needed for numerical implementation. The purpose of this paper is to derive these parameters using composite modelling and experimental data from literature. A full set of constants is estimated for a linear isotropic description of cortical bone as a two-level porous medium. Bone, however, has a wide variety of mechanical and structural properties; with the theoretical relationships described in this note, poroelastic parameters can be derived for other bone types using their specific experimental data sets.

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          Author and article information

          Journal
          Journal of Biomechanics
          Journal of Biomechanics
          Elsevier BV
          00219290
          June 2002
          June 2002
          : 35
          : 6
          : 829-835
          Article
          10.1016/S0021-9290(02)00021-0
          12021003
          7e99f4fb-46e2-4606-8160-0d370932a216
          © 2002

          https://www.elsevier.com/tdm/userlicense/1.0/

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