An, Shuqiang (2013) Computational modelling of fluid load support in articular cartilage. PhD thesis, University of Leeds.
Abstract
Natural articular cartilage is known to be an excellent bearing material
with very low friction coefficient and wear rate. Theoretical and experimental
studies have demonstrated that the interstitial fluid of cartilage is pressurized
considerably under loading to support the applied load, leading to the low
friction coefficient. In this process, collagen fibrils play a vital role to resist
the lateral expansion of cartilage and enhance the pressurization. The
proportion of the total load supported by fluid pressurization in cartilage,
called the fluid load support, is therefore an important parameter in
biotribology and determined as the main aspect of this thesis.
Fibril-reinforced cartilage models were set up to account for the high
pressurization of interstitial fluid. However, the orientation of collagen fibrils
were idealized or simplified; and the models implementing realistic fibril
orientation derived from DT-MRI data did not include viscous effects in both
the solid matrix and the fibril.
This study overcome the limitation of previous models and the major
finding were:
• The peak value of fluid load support in both 2D and 3D fibrilreinforced
models implementing DT-MRI data was increased to greater than
90% from around 60% in the isotropic poroelastic model, due to the
reinforcement by collagen fibril.
• The implementation of the realistic fibril orientation in the 3D fibrilreinforced
model increased the value of peak pore pressure (by 15%)
compared to the uniformly reinforced model while the peak contact pressure
was 4.3% lower, making the peak value of fluid load support increase from
80.4% to 96.7%.
• The rationality to define the principal eigenvector as orientation of the
corresponding primary collagen fibril in the fibril-reinforced models was
verified by the related results.
• The feasibility and reliability of the methodologies to implement DTMRI
data to the fibril-reinforced models were both confirmed in the
modelling process.
Metadata
Supervisors: | Fisher, John and Jin, Zhongmin and Jones, Alison |
---|---|
ISBN: | 978-0-85731-589-2 |
Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering (Leeds) > School of Mechanical Engineering (Leeds) |
Identification Number/EthosID: | uk.bl.ethos.605231 |
Depositing User: | Repository Administrator |
Date Deposited: | 25 Apr 2014 10:44 |
Last Modified: | 03 Sep 2014 10:49 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:5739 |
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