Doctoral Dissertations

Date of Award

5-2017

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Nuclear Engineering

Major Professor

G. Ivan Maldonado

Committee Members

Ondej Chvala, Steve Skutnik, Anthony Mezzacappa

Abstract

Tools that can rapidly compute the isotopic composition of spent nuclear fuel (SNF) are useful for many reasons, including safety and security. Although tools exist to compute approximate isotopic compositions, detailed fuel composition requires reactor simulation that result from normal and off-normal operations. Reactor simulation is typically performed using nodal core simulators. These codes perform their calculations rapidly, but they may not compute isotopic composition.

The Russian designed VVER is a pressurized water reactor that uses hexagonal fuel assemblies with triangularly pitched fuel rods and annular pellets. The international expansion of VVER-1000 reactor technology has motivated a renewed interest in modeling and simulation of these reactors. One source for this operational data is a benchmark proposal of a Ukrainian nuclear power plant. This benchmark has served as a basis for development for improving modeling of the isotopic composition of SNF.

The objective of this work was to extend and improve depletion capabilities of NESTLE, a nodal core simulator, to accurately describe the nuclide inventory of SNF at the assembly and pin level using a hybrid macroscopic and microscopic depletion model. These isotopic inventories were verified by code to code comparison where possible. With these improved capabilities, an exploration of the detailed pin-level isotopic inventory to variations in operational parameters is enabled. This advance provides a powerful tool to assess the impact of excursions in operational conditions on the detailed SNF inventories.

Comments

Much of this work will be or has been published in scientific and engineering journals. Please search the literature for updated research.

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