Level of activity changes increases the fatigue life of the porous magnesium scaffold, as observed in dynamic immersion tests, over time

• Main Authors: Risky Utama Putra, Risky Utama Putra, Basri, Hasan, Akbar Teguh Prakoso, Akbar Teguh Prakoso, Hendri Chandra, Hendri Chandra, Muhammad Imam Ammarullah, Muhammad Imam Ammarullah, Imam Akbar, Imam Akbar, Syahrom, Ardiyansyah, Tunku Kamarul, Tunku Kamarul
• Format: Article
• Language: English
• Published: MDPI 2023
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/107254/1/ArdiyansyahSyahrom2023_LevelofActivityChangesIncreasestheFatigue.pdf; http://eprints.utm.my/107254/; http://dx.doi.org/10.3390/su15010823

In the present study, the effects of human physiological activity levels on the fatigue life of a porous magnesium scaffold have been investigated. First, the dynamic immersion and biomechanical testing are carried out on a porous magnesium scaffold to simulate the physiological conditions. Then, a numerical data analysis and computer simulations predict the implant failure values. A 3D CAD bone scaffold model was used to predict the implant fatigue, based on the micro-tomographic images. This study uses a simulation of solid mechanics and fatigue, based on daily physiological activities, which include walking, running, and climbing stairs, with strains reaching 1000–3500 µm/mm. The porous magnesium scaffold with a porosity of 41% was put through immersion tests for 24, 48, and 72 h in a typical simulated body fluid. Longer immersion times resulted in increased fatigue, with cycles of failure (Nf) observed to decrease from 4.508 × 1022 to 2.286 × 1011 (1.9 × 1011 fold decrease) after 72 hours of immersion with a loading rate of 1000 µm/mm. Activities played an essential role in the rate of implant fatigue, such as demonstrated by the 1.1 × 105 fold increase in the Nf of walking versus stair climbing at 7.603 × 1011 versus 6.858 × 105, respectively. The dynamic immersion tests could establish data on activity levels when an implant fails over time. This information could provide a basis for more robust future implant designs.