A Study on the Optimization of Burnable Poison Material Combinations for Small Long-Lifetime Pressurized Water Reactor Assemblies Based on NSGA-III

Small long-lifetime pressurized water reactors (PWRs) impose higher requirements on the reactivity compensation capacity, power distribution control precision, and long-term burnup adaptability of burnable poisons due to their compact core volume and extended operational lifetime demands. Traditional experience-dependent design of burnable poison combinations struggles to balance multi-objective requirements and easily overlooks the compatibility of different burnable poison combinations, leading to issues such as uneven reactivity release, excessive fluctuations, or insufficient burnup depth in the designed schemes. To address these challenges, this study introduces the reference point-based non-dominated sorting genetic algorithm (NSGA-III) into the optimization design of burnable poison material combinations for small long-lifetime PWRs. Combined with deterministic methods, a multi-objective optimization model is established with core objectives, including controlling initial excess reactivity, reducing reactivity fluctuations, and improving burnup depth. The decision variables include the types of burnable poison materials, their combination ratios, the arrangement of poison-containing fuel plates, and the loading form of the burnable poisons. The calculation results show that the combination of Gd2O3 and B4C exhibits the best comprehensive performance as burnable poisons; the combined application of Er2O3, Eu2O3, Sm2O3, 231Pa, 241Am, 240Pu, and 237Np requires further research in conjunction with core schemes; and Dy2O3 is not suitable as a burnable poison combination material.

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Publication Details

Journal
Energies
Published
2026-04-17
DOI
https://doi.org/10.3390/en19081948
Primary Topic
Nuclear reactor physics and engineering
Type
article
Field-Weighted Citation Impact
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article

A Study on the Optimization of Burnable Poison Material Combinations for Small Long-Lifetime Pressurized Water Reactor Assemblies Based on NSGA-III

Jinsen Xie, Yucheng Ding
Energies
Nuclear reactor physics and engineering
article

A Study on the Optimization of Burnable Poison Material Combinations for Small Long-Lifetime Pressurized Water Reactor Assemblies Based on NSGA-III

Jinsen Xie, Yucheng Ding
article en

Abstract

Small long-lifetime pressurized water reactors (PWRs) impose higher requirements on the reactivity compensation capacity, power distribution control precision, and long-term burnup adaptability of burnable poisons due to their compact core volume and extended operational lifetime demands. Traditional experience-dependent design of burnable poison combinations struggles to balance multi-objective requirements and easily overlooks the compatibility of different burnable poison combinations, leading to issues such as uneven reactivity release, excessive fluctuations, or insufficient burnup depth in the designed schemes. To address these challenges, this study introduces the reference point-based non-dominated sorting genetic algorithm (NSGA-III) into the optimization design of burnable poison material combinations for small long-lifetime PWRs. Combined with deterministic methods, a multi-objective optimization model is established with core objectives, including controlling initial excess reactivity, reducing reactivity fluctuations, and improving burnup depth. The decision variables include the types of burnable poison materials, their combination ratios, the arrangement of poison-containing fuel plates, and the loading form of the burnable poisons. The calculation results show that the combination of Gd2O3 and B4C exhibits the best comprehensive performance as burnable poisons; the combined application of Er2O3, Eu2O3, Sm2O3, 231Pa, 241Am, 240Pu, and 237Np requires further research in conjunction with core schemes; and Dy2O3 is not suitable as a burnable poison combination material.

EnergiesVol. 19(8)
Ministry of Education (TW), University of South China (CN)
Clean water and sanitation
Openalex Percentile: Top 6%
Nuclear reactor physics and engineering
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