Strategic decisions about the deployment of fast reactors and the transition from open to closed nuclear fuel cycle are supported by fuel cycle scenario codes, which are capable of simulating the most important facilities of the nuclear fuel cycle and the material flows between them. However, the models and assumptions being used in the scenario studies are subject to uncertainties, which may have significant impact on the results of such analyses. A fuel cycle simulation program was also developed at the BME Institute of Nuclear Techniques (BME NTI), which uses the FITXS method to calculate fuel depletion in the reactors and was used to investigate the closed fuel cycles of Generation IV fast reactors, as well as transition scenarios involving mixed fleets of fast and MOX fueled thermal reactors. Based on the fitting of one-group cross-sections as polynomial functions of the detailed fuel composition, the FITXS burn-up models can calculate the spent fuel compositions of the reactors fast enough such that parametric and uncertainty studies can be performed with the fuel cycle models.

The main task of the thesis is to acquire a comprehensive knowledge about uncertainty propagation in nuclear fuel cycle simulations from related literature and analyze the impact of different types of uncertainties on the results of the aforementioned and similar closed fuel cycle analyses and transition scenario studies. In order to accomplish these, the student is expected to perform the following tasks:

• Acquire the necessary knowledge in fuel cycle simulations and depletion calculations, including cross-section parametrization and the FITXS method in particular;

• Overview the topic of uncertainty propagation in nuclear fuel cycle simulations from related literature;

• Learn the use of the fuel cycle simulation program developed at the BME NTI;

• Analyze possible methods of uncertainty calculations with the simulation program;

• Perform detailed uncertainty studies in the above mentioned and similar closed fuel cycle analyses and transition scenario studies.