There is great potential for the use of computational tools within the design and test cycle for joint replacement devices. The increasing need for stratified treatments that are more relevant to specific patients, and implant testing under more realistic, less idealised, conditions, will progressively increase the pre-clinical experimental testing work load. If the outcomes of experimental tests can be predicted using low cost computational tools, then these tools can be embedded early in the design cycle, e.g. benchmarking various design concepts, optimising component geometrical features and virtually predicting factors affecting the implant performance. Rapid, predictive tools could also allow population-stratified scenario testing at an early design stage, resulting in devices which are better suited to a patient-specific approach to treatment. The aim of the current study was to demonstrate the ability of a rapid computational analysis tool to predict the behaviour of a total hip replacement (THR) device, specifically the risk of edge loading due to separation under experimental conditions. A series of models of a 36mm BIOLOX® Delta THR bearing (DePuy Synthes, Leeds, UK) were generated to match an experimental simulator study which included a mediolateral spring to cause lateral head separation due to a simulated mediolateral component misalignment of 4mm. A static, rigid, frictionless model was implemented in Python (PyEL, runtime: ∼1m), and results were compared against 1) a critically damped dynamic, rigid, FE model (runtime: ∼10h), 2) a critically damped dynamic, rigid, FE model with friction (µ = 0.05) (runtime: ∼10h), and 3) kinematic experimental test data from a hip simulator (ProSim EM13) under matching settings (runtime: ∼6h). Outputs recorded were the variation of mediolateral separation and force with time.INTRODUCTION
METHODS
