Modeling trabecular microstructure evolution via genetic algorithm

Connecting structure to properties, and optimizing properties by controlling structure is one of the fundamental goals of materials science and engineering. No where is this connection more apparent than with biomaterials, whose unparalleled properties are the result of the evolution via cumulative selection of highly specialized structures. Beyond biomaterials, cumulative selection offers a generalizable model for materials optimization via accumulative of beneficial mutations in a material's genome that improve the properties for a given function. A genetic algorithm is one method for applying the principals of cumulative selection to material's optimization. One of unique property that cumulative selection generated was the ability of trabecular bone to optimize and adjust its structure in vivo in response to changes in its loading conditions. This work presents a model for trabecular microstructure evolution using a genetic algorithm, the same mechanism through which that ability evolved. The algorithm begins by translating a trabecular genome into a developed structure. It then simulates the structure's response under an applied load and selects for the genome which translates into the best structure. The selected genome is then replicated and mutated. Simulations of microstructure evolution consist of iterating through this process across multiple generations. A series of simulations was conducted demonstrating the ability of the algorithm to improve trabecular architecture. The systems tended to converge to a uniform stress distribution, after which additional generations of evolution had no effect on performance. During the simulations it was found that the length of the computation was most sensitive to the number of offspring per generation. Although focused on trabecular microstructure, this work establishes the use of a genetic algorithm as a general tool for material's optimization.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Materials Science and Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Shames, Samuel W. L. (Samuel William Linder)

Advisor dc:contributor.advisor

• W. Craig Carter.

• Materials Science and Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about 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/1721.1/89981

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/89981