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Predicting Friction of Total Joint Replacement Bearings

Academic lead
Greg de Boer​, Mech Eng
Industrial lead
​Mazen Al-Hajjar​, DePuy Synthes
Michael Bryant​, Mech Eng, Ali Ghanbarzadeh, Mech Eng, Alex Frangi, Computing
Project themes
Biomedical Flows

Total joint replacements and the associated orthopaedic technologies are a significant contributor to the needs of a healthy nation and are expected to grow in importance worldwide over the next decade. To reduce this increasing economic burden implants need to be designed so that they function optimally within the body over many millions of load cycles. Current pre-clinical testing is costly and time consuming, computational models therefore provide a huge potential for implant manufacturers to enhance strategies and rapidly predict the performance of new designs. Wear has been well characterised experimentally but engineers are yet to explore the role of friction in device longevity. This is an inherently multiscale problem in which the size, shape and distribution of surface features affect the implant performance overall. This project will therefore deliver a multiscale mixed lubrication model to address these challenges, the complex fluid-structure interaction at the scale of surface asperities will be developed (including elastohydrodynamic lubrication and contact mechanics) and coupled to a tribological model of the implant in operation under representative conditions. The total hip replacement will be used as a case study to investigate friction and wear characteristics. Findings will be validated against concurrent experimentation and previously published datasets.