Abstract

Recently, various researches have revealed the importance of the investigations performed for evaluating mechanical properties and damages of the brain tissues while dealing with the production of surgical ligaments and helmets. Therefore, it is vital to study the structure of the brain both experimentally and numerically. By experimental tests, despite being costly, it is almost impossible to establish stress distribution in micro scale, which causes injury. Micromechanical predictions are effective ways to assess brain behavior. They can be applied to compensate for some experimental test limitations. In this work, a numerical study of the axonal injury in different heterogeneous porcine brain parts with different axon distributions under quasi-static loading is provided. In order to produce a heterogeneous structure, axons are distributed in regular, semi-regular, and irregular patterns inside the representative volume element. To accurately examine the brain tissue time-dependent behavior, a visco-hyperelastic constitutive model is developed. Also, axonal damage is studied under different conditions by applying different levels of load and rate. Because of geometrical complexities, a self-consistent method was applied to study the damage in higher volume fractions of the axon. The results reveal that the regions of the brain enjoying a regular axon distribution would have higher strength. In addition, among the two influential load and loading rate parameters, the brain tissue in all regions shows more sensitivity toward the applying load.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.