The overall purpose of this dissertation is to develop a multi-scale framework that can simulate radiation defect accumulation across a broad range of time and length scales in metals.
In order to accurately describe defect accumulation in heterogeneous microstructures and under complex irradiation conditions, simulation methods are needed that can explicitly account for the effect of non-homogeneous microstructures on damage accumulation. In this dissertation, an advanced simulation tool called spatially resolved stochastic cluster dynamics (SRSCD) is developed for this purpose. The proposed approach relies on solving spatially resolved coupled rate equations of standard cluster dynamics methods in a kinetic Monte Carlo scheme. Large-scale simulations of radiation damage in polycrystalline materials are enabled through several improvements made to this method, including a pseudo-adaptive meshing scheme for cascade implantation and implementation of this method in a synchronous parallel kinetic Monte Carlo framework. The performance of the SRSCD framework developed in this dissertation is assessed by comparison to other simulation methods such as cluster dynamics and object kinetic Monte Carlo and experimental results including helium desorption from thin films and defect accumulation in neutron-irradiated bulk iron. The computational scaling of the parallel framework is also investigated for several test cases of irradiation conditions. SRSCD is next used to investigate radiation damage in three main types of microstructures, using α-iron as a test material: iron thin films, coarse-grained bulk iron, and nanocrystalline iron. SRSCD is used to investigate the mechanisms involved with defect accumulation in irradiated materials, such as effective diffusivity of helium in thin films and the effect of grain boundary sink strength on defect accumulation in nano-grained metals, and to predict defect populations in irradiated materials for comparison with experiments. Particular emphasis is placed on the role of microstructural features such as free surfaces and grain boundaries in influencing damage accumulation. Finally, the methodology developed in this dissertation is applied in the context of multiscale modeling and experimental design. To complete the multi-scale transition between defect-level behavior and macroscopic material property changes caused by irradiation, the relationship between mechanical loading and radiation damage is investigated. The impact of radiation damage on hardening of irradiated materials is investigated by using the results of SRSCD as inputs into polycrystalline crystal plasticity simulations. This is carried out in bulk iron by fitting hardening models to experimental data from neutron irradiation of iron and then used to predict hardening under irradiation conditions beyond what has already been accomplished in experimental studies. In addition, SRSCD is used to demonstrate the temperature shift required to achieve equivalent damage accumulation in irradiation conditions with significantly differing dose rates, such as in the case of using ion irradiation to simulate damage from neutron irradiation. In this dissertation, the development of SRSCD and its application in a multi-scale framework to predict macroscopic material property changes in metals represents a significant improvement over the state of the art due to improved simulations of defect accumulation and direct upscaling of results into polycrystalline plasticity models. The tools and understanding of defect behavior developed here will allow predictive modeling of metal degradation in reactor-relevant damage environments, including the defected microstructure and macroscopic material property changes due to irradiation.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54959 |
| Date | 27 May 2016 |
| Creators | Dunn, Aaron Yehudah |
| Contributors | Capolungo, Laurent |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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