Computational modeling and simulation for projectile impact and indentation of biological tissues and polymers

Understanding the elastic and viscoelastic responses of biological soft tissues and engineered polymer simulants is of great interest to predicting and preventing penetrative injuries. Detailed understanding of the mechanical processes at work could aid in the development and evaluation of protective strategies such as armor and helmets, and repair strategies including robotic surgery or needle-based drug delivery. However, due to the mechanical complexity of so-called "soft tissues," including nonlinear viscoelastic behavior, surface adhesion, material failures and shock effects, the experimental characterization of various soft tissues is challenging and individual mechanical processes are often impossible to decouple without computational models and simulations. This thesis presents two finite element models designed to provide both replicate the results of indentation and impact experiments on synthetic polymers, aimed to decouple competing mechanical characteristics of contact based deformation. The first of these models describes the indentation on polydimethylsiloxane bilayer composites, with the aim of describing the relative effects of a adhesion and viscoelastic properties on the measured deformation response. That model expands on this objective via the analysis of the effects of surface adhesion commonly associated with highly compliant polymers and tissues. The second model attempts to replicate impact of a high velocity projectile on a relatively stiff material, polyurethane urea, and on a comparatively compliant polymer, gelatin hydrogel. These models provide means to simulate, predict and characterize material response, validated by comparison with available experiments. Such validated models can be used to simulate and design new materials as tissue simulants or as protective media that predictably dissipate concentrated mechanical impact.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Biological Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Geiser, Kyle

Advisor dc:contributor.advisor

• Krystyn J. Van Vliet.

• Biological Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/112507

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/112507