The aim of this paper was to propose a novel in silico mixed elasto-hydrodynamic lubrication model with the purpose of wear prediction in Total Hip Replacements (THRs). The model considers the progressive wear contribution in the calculation of the meatus filled by the non-Newtonian synovial fluid. The results were referred to the gait cycle kinematics, calculated by using musculoskeletal multibody software, while the loading was assumed by literature in vivo measurements. The simulations allow evaluating the fluid and the contact pressure fields and the acetabular cup wear over the time. The results were obtained considering a Ultra High Molecular Weight PolyEthylene, UHMWPE, cup and were compared with results from the literature, showing a good agreement in terms of total volume wear of the cup.
In this paper, the procedure to achieve an accurate deformation model of a total hip replacement (THR) was proposed with the aim to obtain a numerical tool to be simply merged into THR elasto-hydrodynamic computational synovial lubrication algorithms. The approach was based on the Finite Element Method (FEM) and was developed in a Matlab code, allowing the definition of the influence matrix and of a boundary conditions vector. It works with linear tetrahedra and performs the displacement calculation for both the acetabular cup and the femoral head, taking into account the anatomical hip relative motion, by coupling them with a cubic interpolation matrix. Two simulations were conducted in order to validate the algorithm and the results were compared with the ones obtained by the commercial software Ansys. The comparison provides a satisfactory agreement in terms of surface deformation, Von Mises stress and strain energy, proving the reliability of the model and the possibility to use the model in the in silico prostheses tribological simulations, avoiding the complexity and the high computational resource requirement coming from the coupling between complex lubrication algorithms and FEM commercial software, and with the possibility to directly act on many key parameter characteristics of the investigated problem.
In the framework of the elasto-hydrodynamic lubrication simulation algorithms of lubricated tribopairs, a key role is played by the chosen deformation model, since it affects the surfaces’ separation, which guarantees the existence of a thin lubricant film thickness, even when the tribo-system is subjected to high loads. The aim of this article is to merge a finite element deformation model based on linear tetrahedra, previously developed by the same authors, within the Reynolds equation solver in the elasto-hydrodynamic mode, with reference to a generic ball in socket lubricated tribo-system. The main novelty of this research is the implementation of the finite element deformation model, allowing the authors to relate the deformation vector to the pressure one through an influence matrix which takes into account the spherical motion of the ball with respect to the socket. The computer code for the problem–solution was developed in a MATLAB environment and simulated a planar motion condition in terms of eccentricity and angular velocity vectors, in order to calculate the meatus fluid pressure field, surfaces’ separation, shear stress, deformation, and wear depth. The integration over time of the output fields led to the time evolution of the load vector, friction torque vector, and wear volume. Moreover, the lubrication algorithm takes into account the fluid non-Newtonian behavior and the surfaces’ progressive geometrical modification over time due to cumulated wear. The obtained results reproduced the classical elasto-hydrodynamic shapes of the involved quantities, following the meatus minimum thickness predicted by the Hamrock–Dowson model; furthermore, it provided information about the mechanical behavior of the whole bodies belonging to the spherical joint thanks to the finite element deformation model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.