Physics-based void nucleation model using discrete dislocation dynamics and cluster dynamics models

Focusing on cavity nucleation, continuum damage mechanics models rely on a posteriori calibration of initial site density and loading conditions. However, empirically calibrated parameters are unreliable due to accelerated testing conditions and cannot be transferred to novel materials. To provide a more accurate description of the relationship between temperature, stress, microstructure, and the kinetics of void nucleation, we develop a physically-based nucleation model by coupling discrete dislocation dynamics (DDD) and cluster dynamics (CD) models. First, a continuum statistical approach developed for this study is shown, demonstrating the ability to model vacancies cluster size evolution as a function of time. Second, the implementation of the DDD method in the study of local energetics within a microstructure is presented. DDD has the capability to accurately model complex dislocation networks permitting a high-fidelity account of the local energy landscape arising from defect-defect interactions. Lastly, multiple potential nucleation sites in bulk are examined for nucleation. Our results are consistent with experimental observations indicating that nucleation is highly improbable in bulk

Physics-based void nucleation model using discrete dislocation dynamics and cluster dynamics models

Focusing on cavity nucleation, continuum damage mechanics models rely on a posteriori calibration of initial site density and loading conditions. However, empirically calibrated parameters are unreliable due to accelerated testing conditions and cannot be transferred to novel materials. To provide a more accurate description of the relationship between temperature, stress, microstructure, and the kinetics of void nucleation, we develop a physically-based nucleation model by coupling discrete dislocation dynamics (DDD) and cluster dynamics (CD) models. First, a continuum statistical approach developed for this study is shown, demonstrating the ability to model vacancies cluster size evolution as a function of time. Second, the implementation of the DDD method in the study of local energetics within a microstructure is presented. DDD has the capability to accurately model complex dislocation networks permitting a high-fidelity account of the local energy landscape arising from defect-defect interactions. Lastly, multiple potential nucleation sites in bulk are examined for nucleation. Our results are consistent with experimental observations indicating that nucleation is highly improbable in bulk