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Computational method for bearing surface wear prediction in total hip replacements

Toh, SM, Ashkanfar, A, English, R and Rothwell, G (2021) Computational method for bearing surface wear prediction in total hip replacements. Journal of the Mechanical Behavior of Biomedical Materials, 119. ISSN 1751-6161

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Abstract

Total hip replacement (THR) is a revolutionary treatment when a hip joint becomes severely damaged. Wear is known as one of the main reasons for THR failure. Current experimental techniques to investigate the wear at the bearing surfaces of THRs are time-consuming, complicated and expensive. In this study, an in-house fretting wear algorithm has been further developed to investigate the wear damage that occurs on bearing surfaces of THRs and its consequence on the longevity of the implants. A 3D finite element model has been created with a 36 mm diameter Cobalt–Chromium femoral head and a 4 mm thick cross-linked polyethylene bearing liner. A gait loading cycle was used to simulate walking for up to 5 million cycles (Mc). The wear algorithm extracts relative displacements and contact shear stresses from the finite element package to predict the linear and volumetric wear rates. This method is shown to have modelled the evolution of wear effectively and found it to be similar to those from experimental analyses. The linear and volumetric wear per million cycles predicted in this study were 0.0375mm/Mc and 33.6mm3/Mc which are comparable to those measured in-vivo THRs. The wear patterns obtained from this study are also comparable to the wear patterns shown on available conventional polyethylene liners. This method can be used to further aid in the design and clinical technique to reduce wear rate in THRs.

Item Type: Article
Uncontrolled Keywords: 0903 Biomedical Engineering, 0912 Materials Engineering, 0913 Mechanical Engineering
Subjects: R Medicine > R Medicine (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Engineering
Publisher: Elsevier BV
Date Deposited: 14 Apr 2021 10:49
Last Modified: 04 Sep 2021 05:36
DOI or Identification number: 10.1016/j.jmbbm.2021.104507
URI: https://researchonline.ljmu.ac.uk/id/eprint/14799

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