Literature DB >> 16687782

Mathematical description of stress relaxation of bovine femoral cortical bone.

Toshiya Iyo1, Naoki Sasaki, Yasuyuki Maki, Mitsuo Nakata.   

Abstract

In 1993 we proposed an empirical formula for describing the relaxation modulus of cortical bone based on the results of stress relaxation experiments performed for 1 x 10(5) sec: [E(t) = E0{A exp[ -(t/tau1)beta] + (1 - A) exp(-t/tau2)}, (0 < A, beta <1 and tau1 << tau2) where E0 is the initial value of the relaxation modulus, A is the portion of the first term, tau1 and tau2 are characteristic relaxation times, and beta is a shape factor [Sasaki et al., J. Biomechanics 26 (1993), 1369]. Although the relaxation properties of bone under various external conditions were described well by the above equation, recent experimental results have indicated some limitations in its application. In order to construct an empirical formula for the relaxation modulus of cortical bone that has a high degree of completeness, stress relaxation experiments were performed for 6 x 10(5) seconds. The second term in the equation was determined as an apparently linear portion in a log E(t) vs t plot at t>1 x 10(4) sec. The same plot for experiments performed for 6 x 10(5) seconds revealed that the linear portion corresponding to the second term was in fact a curve with a large radius of curvature. On the basis of this fact, we proposed a second improved empirical equation E(t) = E0{A exp [ -(t/tau1)beta] + (1 - A) exp[-(t/tau2)gamma]}, (0<A, beta, gamma <1) to describe the stress relaxation of cortical bone. The early stage of the stress relaxation process, which could not be expressed by the first, is well described by the second equation.

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Year:  2006        PMID: 16687782

Source DB:  PubMed          Journal:  Biorheology        ISSN: 0006-355X            Impact factor:   1.875


  1 in total

1.  A mathematical model for fitting and predicting relaxation modulus and simulating viscoelastic responses.

Authors:  Qinwu Xu; Björn Engquist
Journal:  Proc Math Phys Eng Sci       Date:  2018-05-16       Impact factor: 2.704

  1 in total

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