A Computational Parametric Design Approach for Orthopedic Implants Under Highly Nonlinear Conditions
Volume 4: Biomedical and Biotechnology; Design, Systems, and Complexity(2022)
Abstract
Abstract The ability to perform computational parametric studies can reduce design loops and thus the design development timeline. The models also need to be thoroughly verified and validated as per standards such as ASME VVUQ 40 to ensure their accuracy relative to the device design, its configuration and application. As a case study, this paper presents the development of a computational approach to simulate off axis screw insertion followed by cantilever loading on a predicate/on-market trauma locking plate implant. Due to off-axis insertion a high probability of cross threading between the threads of the screw head and the plate exists. This can introduce significant damage to the threads on both the screw as well as the plate which then potentially impacts the load bearing capacity of the screw-plate interface. This paper compares two simulation approaches i) Lagrangian approach with element deletion and ii) Coupled Eulerian Lagrangian (CEL). Simulations are performed using a general-purpose finite element code ABAQUS® along with an explicit time integration approach. The modeling approach is validated by comparing the predicted response of the screw-plate interface with cantilever loading results from laboratory tests. The thread deformation profiles are compared to the observed thread damage from testing. Effect of simulation parameters such as mesh density and mass scaling for an explicit quasi-static simulation are studied. The results show potential in continuing further investigations to enable employing the models as tools to perform parametric studies. For the insertion configurations simulated, the models are able to simulate the desired screw head prominence. The deformation profiles and the regions with thread damage as predicted by the analysis compare well with the observed thread damage during the tests. When the simulations diverge from the observed test data, the reasons for this variability are investigated and potential solutions or additional tests/simulations are recommended. The paper highlights the challenges and potential evaluation approaches while attempting to develop a robust computational methodology which can be employed for design development when specifically applied to highly nonlinear complex loading scenarios.
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