A systematic AMF–FEM coupled method for the thermo-elasto-plastic contact analysis of the plasma sprayed HA-coated biocomposite
Source abstract
Abstract
Hydroxyapatite (HA) coated Ti-6Al-4V alloy biocomposite has been accepted as one of the most promising implant materials for orthopaedic and dental applications because of its favorable biocompatibility and mechanical properties. After the plasma sprayed HA composite coating on titanium alloy substrate biocomposite was prepared, a novel meshless numerical analysis method of the coupled adaptive meshfree method and finite element method (AMF–FEM) is developed for the simulation of the thermo-elasto-plastic contact problems of the biocomposites in this paper. The adaptive meshfree method based on strain energy gradient is used in the concerned contact domain, and FEM is used in the non-contact domain to overcome the difficulties of the meshfree method and improve the calculation efficiency. The thermo-elasto-plastic contact model using the incremental-initial stiffness method, error estimation and the local adaptive refinement strategy for the AMF–FEM method are combined. The AMF–FEM thermo-elasto-plastic model takes into account the temperature variation, micro plastic flow, the thermo-elasto-plastic coupling behavior and the strain-hardening property of the materials. The examples of the elastic/thermal-elastic contact of real HA-coated rough surfaces using the AMF–FEM is studied for two biomaterial models, respectively. The results all show that the AMF–FEM solutions are accurate, efficient, and can be widely applied to different thermo-elasto-plastic contact multi-layer biomaterial models considering different geometric parameter, material parameter, thermal and friction properties.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Numerical methods in engineering · Mechanical stress and fatigue analysis · Adhesion, Friction, and Surface Interactions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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