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Research Article

AP-1000 fuel assembly performance with UO2 and UO2/U3Si2 fuels and silicon carbide cladding from the viewpoint of neutronics

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Pages 6830-6840 | Received 15 Dec 2023, Accepted 13 May 2024, Published online: 22 May 2024
 

ABSTRACT

Accident Tolerate Fuels have been highly researched since the Fukushima disaster. To improve the safety of the AP-1000 fuel assembly, an advanced fuel, UO2/U3Si2, is considered. In addition, the silicon carbide (SiC) cladding that has the capability of reducing oxidation is compared with the baseline Zircaloy for AP-1000 fuel assembly along with the two different fuel cases (UO2 and UO2-U3Si2). The present study focuses on the neutronic performance of the UO2/U3Si2 fuel and thus the main neutronic parameters such as the fuel cycle length, pin power distribution, atom density evolution of main isotopes, and the reactivity feedback coefficients are evaluated. An increase of 6.72% in the criticality period is introduced when 70%UO2-30%U3Si2 fuel with SiC cladding is considered. The pin power peaking factors, fuel temperature coefficients, and moderator temperature coefficients of the proposed fuel result in very few changes. For instance, the maximum pin power distribution difference between 70%UO2-30%U3Si2 and UO2 fuel with SiC cladding is 0.001, which is negligible. Thus, its performance is as good as the traditional UO2 fuel from the neutronic aspects and controlling power distribution.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported that there is no funding associated with the work featured in this article.

Notes on contributors

Farrokh Khoshahval

Farrokh Khoshahval is with Reactor and Nuclear Safety Research School, Nuclear Science and Technology Research Institute (NSTRI). He received his BSc degree in Electrical Engineering and Master’s and PhD degrees in Nuclear Engineering from Shahid Beheshti University, Iran. His research areas include neutronic, thermal-hydraulic analysis, nuclear fuel management, and heuristic optimization methods.

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