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1. Nuclear data uncertainty reduction for advanced reactor modeling and simulation through Bayesian data assimilation

open_access
Open Access
Author:
Vidal Soares, Andre
Title:
Nuclear data uncertainty reduction for advanced reactor modeling and simulation through Bayesian data assimilation
Graduate Program:
Nuclear Engineering
Keywords:
molten salt reactor; nuclear data uncertainty; data assimilation; Bayesian Monte Carlo; nuclear material control and accountability; safeguards
File:
Download PhD_thesis_6-26-2024.pdf
Committee Members:
Dipanjan Pan, Professor in Charge/Director of Graduate Studies
Amanda Johnsen, Chair & Dissertation Advisor
Arthur Motta, Major Field Member
Elia Merzari, Major Field Member
William Walters, Special Member
Mauricio Nascimento, Outside Unit & Field Member

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