Research on a Data-Driven Fast Calculation Method for Power Distribution in Small Nuclear Power Reactor Core

Small nuclear power reactors have small core dimensions, frequent power changes, and more severe power distortion compared to nuclear power stations. However, their core has fewer measurement points, making it difficult to observe their core power distribution. High-precision physical calculation programs can accurately calculate the core power distribution, but the real-time performance of the calculation is poor, which is not conducive to online use. In this study, based on physical computing programs, the power distribution spectrum library of small nuclear power reactors under different operating conditions is calculated, and artificial intelligence algorithms are designed. A data-driven model for the proxy relationship between operating state parameters and core power distribution is trained and constructed to achieve rapid calculation and online support of core power distribution, which improves the level of online safety supervision of small power reactors. Numerical experiments show that this method has high accuracy and good robustness, and can meet the requirements of small nuclear power reactor operation safety support. This research is based on a data-driven proxy model and has achieved fast computation of power distribution in the fuel cores of small modular reactors. It addresses the issue of insufficient real-time performance of high-precision physical programs and has important significance for the safe operation of reactors.

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Publication Details

Journal
Processes
Published
2025-03-13
DOI
https://doi.org/10.3390/pr13030841
Primary Topic
Nuclear reactor physics and engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on a Data-Driven Fast Calculation Method for Power Distribution in Small Nuclear Power Reactor Core

Xiaolong Wang, Cong Zhang, Song Li, Yongfa Zhang
Processes
Nuclear reactor physics and engineering
article

Research on a Data-Driven Fast Calculation Method for Power Distribution in Small Nuclear Power Reactor Core

Xiaolong Wang, Cong Zhang, Song Li, Yongfa Zhang
article en

Abstract

Small nuclear power reactors have small core dimensions, frequent power changes, and more severe power distortion compared to nuclear power stations. However, their core has fewer measurement points, making it difficult to observe their core power distribution. High-precision physical calculation programs can accurately calculate the core power distribution, but the real-time performance of the calculation is poor, which is not conducive to online use. In this study, based on physical computing programs, the power distribution spectrum library of small nuclear power reactors under different operating conditions is calculated, and artificial intelligence algorithms are designed. A data-driven model for the proxy relationship between operating state parameters and core power distribution is trained and constructed to achieve rapid calculation and online support of core power distribution, which improves the level of online safety supervision of small power reactors. Numerical experiments show that this method has high accuracy and good robustness, and can meet the requirements of small nuclear power reactor operation safety support. This research is based on a data-driven proxy model and has achieved fast computation of power distribution in the fuel cores of small modular reactors. It addresses the issue of insufficient real-time performance of high-precision physical programs and has important significance for the safe operation of reactors.

ProcessesVol. 13(3)
Naval University of Engineering (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Hubei Province
Openalex Percentile: Top 94%
Nuclear reactor physics and engineering
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Research on a Data-Driven Fast Calculation Method for Power Distribution in Small Nuclear Power Reactor Core — Xiaolong Wang, Cong Zhang, et al. · Processes (2025) | TGRS Research Map | TGRS