The ultra-high molecular weight polyethylene (UHMWPE) is a popular biomaterial. Pre-clinical evaluation of UHMWPE in terms of wear resistance is extremely important to avoid the effect of implant loosening after implantation. This work proposed an efficient and accurate computational modelling approach to predict elasto-plastic properties at meso-scale, and further integrated at macro-scale to predict adhesive wear in dry tribo-pairs condition. The representative volume element (RVE) based finite element technique was used to predict elastoplastic behaviour of nano-hydroxyapatite (nHA) reinforced UHMWPE composite. The predicted values were validated experimentally and applied as a material property of pin during a numerical investigation of adhesive wear by a macro-scale modelling approach. The CoCr alloy was taken as the counter disc material. The integration of Archard's wear model and user-subroutine was done for numerical prediction of wear. The numerically obtained wear rate and friction coefficient results were validated experimentally by a pin on the disc wear setup under dry conditions. The fabrication of the specimen for validation was done by microwave-assisted compression moulding (MACM). The microstructural investigation of worn surfaces was done by scanning electron microscopy (SEM) to understand the mechanism of adhesive wear. The surface mapping of worn surfaces was done using an optical profilometer to observe the surface roughness after adhesive wear. Biocompatibility of the composite material was confirmed by In-vitro direct contact cytotoxicity test
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