Research PapersNo Access

A NUMERICAL TECHNIQUE TO EVALUATE THE FLEXURAL STIFFNESS OF LONG BONES AFFECTED BY CRACKS AND POROSITY

HADI MOHAMMADI

Biomedical Engineering Graduate Program, University of Western Ontario, London, Ontario N6A 5B9, Canada

Corresponding author.

Search for more papers by this author

FERESHTEH BAHRAMIAN

Biomedical Engineering Graduate Program, University of Western Ontario, London, Ontario N6A 5B9, Canada

Search for more papers by this author

KIBRET MEQUANINT

Department of Chemical and Biochemical Engineering, University of Western Ontario, London, Ontario, Canada

Search for more papers by this author

, and

AMIN RIZKALLA

Department of Chemical and Biochemical Engineering, University of Western Ontario, London, Ontario, Canada

Search for more papers by this author

https://doi.org/10.1142/S021951941000368XCited by:1 (Source: Crossref)

Abstract

Bone maintains its structure through a constant process of resorption and formation, in a process called bone remodeling. An imbalance in this process caused by disease, abnormal mechanical demands, or fatigue may predispose bone to fracture injuries. Increase in bone resorption can increase the number of surface cracks and structural porosity of the bone and thus change its stiffness properties. In this study, a computational technique is proposed to investigate the stiffness properties in long bones based on dynamic responses. As the first attempt, defects such as porosity and cracks are detected based on changes in stiffness properties of the sample. The least square algorithm and the finite element method are used as tools in this study. The Wilson-θ numerical method is employed to generate artificially experimental results for acceleration vectors. The data obtained from the artificial experiment is later employed to the proposed computational investigation model as raw data.

Keywords:

References

R. Hart , Bone Mechanics Handbook , ed. S. Cowin ( CRC Press , 2001 ) . Google Scholar
C. Qua, Q. H. Qinb and Y. Kanga, J. Biomater. 27(12), 4050 (2006). Crossref, Web of Science, Google Scholar
C. R. Jacobset al., J. Biomech. 30, 603 (1997), DOI: 10.1016/S0021-9290(96)00189-3. Crossref, Web of Science, Google Scholar
M. G. Mullender, R. Huiskes and H. Weinans, J. Biomech. 27, 1389 (1994), DOI: 10.1016/0021-9290(94)90049-3. Crossref, Web of Science, Google Scholar
P. J. Prendergast and R. Huiskes, J. Biomech. Eng. 118, 240 (1996), DOI: 10.1115/1.2795966. Crossref, Web of Science, Google Scholar
M. Zidi and S. Ramtani, J. Biomech. 32, 743 (1999), DOI: 10.1016/S0021-9290(99)00033-0. Crossref, Web of Science, Google Scholar
S. Ramtani and M. Zidi, Mech. Res. Commun. 26, 701 (1999), DOI: 10.1016/S0093-6413(99)00081-6. Crossref, Web of Science, Google Scholar
S. Ramtani and M. Zidi, Eur. Phys. J. AP. 8, 257 (1999), DOI: 10.1051/epjap:1999254. Crossref, Web of Science, Google Scholar
S. Ramtani and M. Zidi, J. Biomech. 34, 471 (2001), DOI: 10.1016/S0021-9290(00)00215-3. Crossref, Web of Science, Google Scholar
V. A. Papathanasopoulouet al., Int. J. Eng. Sci. 42, 511 (2002). Web of Science, Google Scholar
V. A. Papathanasopoulou, D. I. Fotiadis and C. V. Massalas, Int. J. Eng. Sci. 42, 395 (2004), DOI: 10.1016/S0020-7225(03)00070-3. Crossref, Web of Science, Google Scholar
G. Rouhiet al., FORMA 19, 165 (2004). Google Scholar
S. L. Y. Wooet al., J. Bone. Int. Surg. 780 (1981). Google Scholar
H. K. Uthoft and Z. F. G. Jaworski, J. Bone. Int. Surg. B 60, 42 (1978). Google Scholar
F. G. Jaworski, M. Liskova-kiar and H. K. Uthoft, J. Bone. Int. Surg. 104 (1980). Google Scholar
S. C. Cowinet al., J. Biomech. 471 (1981), DOI: 10.1016/0021-9290(81)90097-X. Google Scholar
J. C. Misraet al., Comput. Math. Appl. 3 (1992), DOI: 10.1016/0898-1221(92)90150-G. Google Scholar
D. B. Burret al., J. Bone. Joint. Surg. 72, 370 (1990). Web of Science, Google Scholar
S. Mori and D. B. Burr, Bone 14, 103 (1993), DOI: 10.1016/8756-3282(93)90235-3. Crossref, Web of Science, Google Scholar
R. B. Martin, Bone 30, 8 (2002), DOI: 10.1016/S8756-3282(01)00620-2. Crossref, Web of Science, Google Scholar
R. B. Martin, Calcif. Tissue. Int. 73, 101 (2003), DOI: 10.1007/s00223-002-1059-9. Crossref, Web of Science, Google Scholar
T. L. Foutz, G. N. Rowland and M. D. Evans, Trans. ASAE (USA) 40(6), 1727 (1997). Crossref, Google Scholar
U. Pabst and P. Hagedon, ASME 59, 99 (1993). Google Scholar
B. E. Lindholm and R. L. West, System identification of finite element modeling parameters using experimental spatial dynamic modeling, 1st International Conference of Vibration Measurements by Laser Technique450 (Ancona, Italy, 1994) p. 462. Google Scholar
C. Flanigan, Correction of finite element method using mode shapes design sensitivity, Proceeding of 9th International Modal Analysis Conference, Society of Experimental Mechanics (1991) pp. 84–88. Google Scholar
A. M. Kabe, AIAA. J. 23, 1431 (1985), DOI: 10.2514/3.9103. Crossref, Google Scholar
L. Cuiping and S. W. Smith, J. Guid. Control. Dyn. 419 (1995). Google Scholar
M. Zehn , F. Wahl and G. Schmidt , Verification and Adjustment of Dynamic Structural Finite Element Models by Experimental Model Analysis Data, Computational Methods and Experimental Measurements VII , eds. G. M. Carbmango and C. A. Brebia ( Computational Mechanics Publications , Southampton , 1995 ) . Google Scholar
H. Mohammadi, J. Appl. Biomech. 25(3), 271 (2009). Crossref, Web of Science, Google Scholar
J. H. Ferziger , Numerical Methods for Engineering Applications ( Wiley-Interscience , 1998 ) . Google Scholar
R. Fedida et al. , Femure mechanical simulation using high order finite element analysis with continuous mechanical properties , 2nd International Conference on Computational Bioengineering ( 2005 ) . Google Scholar