AN EXPERIMENTALLY VALIDATED COMPUTATIONAL MODEL FOR THE DEGRADATION AND FRACTURE OF MAGNESIUM-BASED IMPLANTS IN A CHEMICALLY CORROSIVE ENVIRONMENT
Date of Award
Open Access Master's Thesis
Master of Science in Mechanical Engineering (MS)
Administrative Home Department
Department of Mechanical Engineering-Engineering Mechanics
Committee Member 1
Committee Member 2
Roger Guillory II
In the orthopedic and cardiovascular fields there is a growing interest for biodegradable implants, which can be naturally degraded in the body environment over time so that no extraction surgery is required. These implants must be designed to maintain their strength until the fracture has healed in the body, which could be influenced by many factors such as -the patient’s age, activities, body weight, pre-existing conditions etc. Hence, an ideal implant design should be done on a patient-by-patient basis. In the present work, a computational model is developed to predict the degradation and fracture of magnesium-based implants in a stress-coupled chemically corrosive environment to better predict their lifespan. The degradation is modeled as a diffusion-driven dissolution of magnesium from the implant into the surrounding fluid simulating the body environment, and as the concentration of magnesium decreases in the implant, its mechanical integrity weakens. A phase-field fracture model is also implemented to predict the initiation and growth of cracks in the specimen. To validate the model, experiments are conducted by exposing pure magnesium specimens to an artificial body solution for various durations of time and subsequently tensile testing them. The model is numerically implemented in finite elements and the parameters are calibrated from experiments to successfully predict the fracture/degradation response of the Mg-implants under mechanical loads.
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Ousdigian, Mark M., "AN EXPERIMENTALLY VALIDATED COMPUTATIONAL MODEL FOR THE DEGRADATION AND FRACTURE OF MAGNESIUM-BASED IMPLANTS IN A CHEMICALLY CORROSIVE ENVIRONMENT", Open Access Master's Thesis, Michigan Technological University, 2023.