LEU+ to HALEU nuclear fuel cycle transitions and dynamic reactor models

Ryan, Nathan Sean

Permalink

https://hdl.handle.net/2142/129324 Copy

Description

Title

LEU+ to HALEU nuclear fuel cycle transitions and dynamic reactor models

Author(s)

Ryan, Nathan Sean

Issue Date

2025-05-07

Director of Research (if dissertation) or Advisor (if thesis)

• Munk, Madicken
• Huff, Kathryn D

Committee Member(s)

Uddin, Rizwan

Department of Study

Nuclear, Plasma, & Rad Engr

Discipline

Nuclear, Plasma, Radiolgc Engr

Degree Granting Institution

University of Illinois Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Cyclus
• TRISO
• HALEU
• LEU+
• LEU Plus
• Serpent
• Nuclear Fuel Cycle
• Memory Efficiency
• Dynamic Power
• Fuel Trading
• Reactor Deployment
• Advanced Reactors

Abstract

Understanding the nuclear fuel cycle is crucial when designing sustainable and efficient nuclear energy systems. This thesis studies timely transition scenarios for fleets of Micro Modular Reactors (MMRs), X-Energy Xe-100s (Xe-100s), and AP1000s where low-enriched uranium plus (LEU+) fuel delays the demand for high-assay low-enriched uranium (HALEU) for the TRi-structural ISOtropic (TRISO) fueled reactors through a greedy, random, and initially random then greedy deployment scheme to meet energy demand growths from the U.S. Department of Energy (DOE) and U.S. Energy Information Administration (EIA). Using the open-source code Cyclus to model fuel cycles and the Monte Carlo code Serpent to perform neutronics calculations for the Xe-100 and USNC MMR, the results show that the reactor deployment scheme impacts the separative work units (SWU) required to meet energy demand. The greedy scheme, which prefers the highest capacity reactors, leads to the most significant increase in SWU for AP1000 low-enriched uranium (LEU), while the random and initially random then greedy schemes result in more consistent increases across fuel types. By evaluating the masses of fresh and used fuel, SWU, the number of reactors, and how well each simulation meets the projected energy demand, this thesis provides a comprehensive understanding of the impact of reactor deployment schemes on the nuclear fuel cycle. Additionally, this thesis examines the computational complexity of reactor fuel trading and removes assumptions about reactor power. The Trading On-Demand (TOD) reactor reduces the number of instructions in a simulation by trading fuel only when needed, while the Dynamic Power Reactor (DPR) allows for flexible power output to mirror historical or projected capacity factors. The results show that improving reactor models and simulating fuel cycle transitions leads to more efficient reactor deployment and fuel cycle design.

Graduation Semester

2025-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/129324

Copyright and License Information

© 2025 by Nathan Sean Ryan. All rights reserved.

Owning Collections