Doctoral Dissertations

Orcid ID


Date of Award


Degree Type


Degree Name

Doctor of Philosophy


Nuclear Engineering

Major Professor

Brian David Wirth

Committee Members

Brian David Wirth, Ivan Maldonado, William John Weber, Steven John Zinkle, Anders David Andersson, Benjamin Collins


Computational modeling of Chalk River Undesirable Deposits (CRUD) allows for the prediction of associated phenomena that impact nuclear power plant performance, reliability, and safety. It also provides insight into the physical mechanisms by which CRUD forms and affects plant performance. A major concern in pressurized water reactors (PWRs) is Axial Offset Anomaly (AOA) which is caused by CRUD’s proficiency at trapping boron within the reactor core. The ability to predict AOA and other phenomena requires a detailed explanation of the chemical composition of CRUD. By pairing computational models that can simulate the structure and species trapping with detailed thermochemical models, the compounds that makeup CRUD are determined. Among these thermodynamically predicted compounds is Ni2FeBO5, a mineral named bonaccordite, the formation of which provides a boron retention mechanism. Accordingly, bonaccordite has been found in CRUD samples from fuel linked to very extreme AOA. In this dissertation, thermochemical models are detailed for PWR primary loop chemistry up to the saturation temperature and are implemented using CALPHAD modeling. Likely solid precipitation reactions are identified, and those reactions are incorporated into the multiphysics continuum modeling code MAMBA. An assessment of the kinetic rates of the reactions are determined by Bayesian calibration of the MAMBA model using observational data from CRUD samples. The modeling is able to demonstrate the composition of CRUD scrapes obtained from plant data. This model contributes to the understanding of CRUD formation and composition and allows for the prediction of phenomena such as AOA.

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