On fatigue failure prediction of prosthetic devices through XFEM analysis
Source abstract
Abstract
Abstract While prosthetic devices have been extensively used to treat a wide range of human diseases and injuries, failure of these devices due to fatigue under cyclic loading has been recognized as a primary concern on therapeutic longevity. Experimental testing has long been a dominant approach to characterizing the fatigue behavior of prosthetic devices. However, experimental methods could be of multiple shortcomings such as their restrictive nature in-vivo in medical studies and limitations of extrapolating the testing results. This study develops a numerical approach for modeling fatigue failure in some commonly-used osteofixation devices that are implanted to support various major bone defects/trauma and fractures. The eXtended Finite Element Method (XFEM) is employed herein to model fatigue crack formation and propagation as per level set functions to suppress the need for re-meshing. For validation purpose, a benchmark problem involving a modified compact tension structure is first carried out, in which the modeling results are compared with the relevant experimental data to demonstrate the effectiveness of the proposed XFEM approach. Further, two representative orthopedic examples are studied for characterizing the fatigue behavior of a femoral osteofixation plate and a mandibular reconstruction mini-plate, respectively. The results reveal that healing/remodeling of grafted bone as well as tissue ingrowth to the scaffold have significant bearing on fatigue life of fixation plates. This study showcases a valuable approach for predicting fatigue failure of prosthetic devices in-silico, thereby providing an effective tool for design optimization of patient-specific prosthetic devices to ensure their longevity.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Orthopaedic implants and arthroplasty · Bone fractures and treatments · Fatigue and fracture mechanics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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