GP and GP-FEA Multiscale Modeling: Model Size Effects and Applications
Date
2015-04
Authors
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Journal ISSN
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Publisher
Kazuo Inamori School of Engineering at Alfred University.
Abstract
Multiscale analysis is the study that bridges the gap between theory and
experiment via numerical simulation and works to couple material behavior across
disparate length and time scales. There is a growing need for techniques that operate
within this regime as progressing technology requires ever more accurate and
fundamental understanding of their materials. Multiscale analysis seeks to offer
atomistically-based informed solutions to the leading technological problems in materials
science. In this thesis the Generalized Particle (GP) method is validated with elasticity
solutions and coupled to a Finite Element Mesh capable of efficiently modelling in the
micro-scale with atomistic detail at local regions such as crack tips. This coupling method
(GP-FEA) is used to investigate model size effects on local atomistic phenomena. Size
effects were found for both elastic and inelastic (crack propagation) pre-cracked
crystalline Iron samples. For these examples it was seen that models 500nm and larger
were consistent with Linear Elastic Fracture Mechanics predictions for the displacement
filed around a crack tip for a given load, however models smaller than 500nm
underestimated the amount of deformation and had smaller zones of crack-tip phase
transformation causing a lower toughness. These results show that the model size used in
simulation and modelling must be large enough for the interesting atomistic phenomena
to be accurate. This work sets the stage for further model size research based on atomistic
analyses in hopes of proving a useful model size guideline for future work to be more
accurate.
In addition to this research the multiscale program and numerous tools and
utilities developed to acquire this data are explained and examples given. Those scientists
interested in particle based dynamic simulation methods and analyses are encouraged to
peruse the latter chapters and appendices for detailed information regarding the specific
algorithms used and the structure of the programs. This additional rich information is
appended to encourage further work and development in the field of multiscale analysis.
Description
Advisory committee members: S.K. Sundaram, Yiquan Wu. Dissertation completed in partial fulfillment of the requirements for the degree of Masters of Science in Mechanical Engineering at the Kazuo Inamori School of Engineering at Alfred University.
Type
Thesis