NUMERICAL PREDICTION OF THE COMPONENT-RATIO-DEPENDENT COMPRESSIVE STRENGTH OF BONE CEMENT
Anna Machrowska, Robert Karpiński, Józef Jonak, Jakub Szabelski
Abstract
Changes in the compression strength of the PMMA bone cement with a variable powder/liquid component mix ratio were investigated. The strength test data served to develop basic mathematical models and an artificial neural network was employed for strength predictions. The empirical and numerical results were compared to determine modelling errors and assess the effectiveness of the proposed methods and models. The advantages and disadvantages of mathematical modelling are discussed.
Topics & Concepts
Computer scienceCompressive strengthArtificial neural networkComponent (thermodynamics)CementExperimental dataBone cementMaterials scienceComposite materialMachine learningStatisticsMathematicsPhysicsThermodynamicsOrthopaedic implants and arthroplastyAdvanced machining processes and optimizationTotal Knee Arthroplasty Outcomes