Download or read book Liquid-fueled Molten Salt Reactor Modeling and Uncertainty Analysis for Safeguards Purposes written by Andre Vidal Soares and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the recent interest in advanced nuclear reactors, the need for developing nuclear material accounting strategies arise. Especially in liquid-fueled molten salt reactors, which preclude the ability to count fixed amount of material in a discrete way, as opposed to the traditional counting method widely used in the current nuclear fleet. Usually, these reactor concepts involve online fuel processing where fuel and its products flow within many streams along the plant. In computational modeling, this feature requires high fidelity depletion schemes, including the addition of feed and removal capabilities that can simulate their regular operation. Estimating isotopic inventory under regular and diversion scenarios would provide an insight on which reactor parameters could be tracked to timely detect diversion of special nuclear material. To achieve this, a depletion model was developed for the Molten Salt Demonstration Reactor (with minor adaptations) in Serpent 2 and SCALE. Feed and removal capabilities were implemented in the Serpent latest release and is under testing in SCALE 6.3 beta versions. Plutonium diversion scenarios are modeled and their impact on regular operation of the reactor is analyzed. The SCALE module Sampler is used to estimate nuclear data uncertainties propagated along the depletion interval. Several isotopes presented changes in their concentrations given a 10SQ plutonium diversion protracted scenario. Some examples are fission products such as 89Sr (1.06% change and 0.58% uncertainty), 91Y (1.92% change and 0.43% uncertainty), 113Cd (-5.00% change and 3.31% uncertainty), 151Eu (-3.84% change and 2.70% uncertainty) and also actinides like 241Am (-6.88% change and 2.23% uncertainty), 242mAm (-6.22% change and 4.88% uncertainty) and 242Cm (-4.50% change and 3.84% uncertainty). Preliminary sensitivity analyses were performed using TSUNAMI and Sampler. Results revealed that 238U(n,[gamma]) plays an important role in contributing to the uncertainty in parameters (e.g., k-inf) and nuclide concentrations (e.g., 239Pu and 241Pu). Future work includes the full analyses of scenarios - including abrupt ones, which are already modeled, and a comprehensive sensitivity study on nuclide concentrations - including fission products and higher actinides. Moreover, methods to improve nuclear covariance data - guided by the sensitivity study - will also be pursued using Bayesian methods and machine learning techniques.