Study on a Data-Enabled Physics-Informed Reactor Physics Operational Digital Twin

Gong Helin; Chen Zhang; Li Qing; Cheng Sibo

doi:10.13832/j.jnpe.2021.S2.0048

Volume 42 Issue S2

Dec. 2021

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Article Navigation > Nuclear Power Engineering > 2021 > 42(S2): 48-53

Gong Helin, Chen Zhang, Li Qing, Cheng Sibo. Study on a Data-Enabled Physics-Informed Reactor Physics Operational Digital Twin[J]. Nuclear Power Engineering, 2021, 42(S2): 48-53. doi: 10.13832/j.jnpe.2021.S2.0048

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Gong Helin, Chen Zhang, Li Qing, Cheng Sibo. Study on a Data-Enabled Physics-Informed Reactor Physics Operational Digital Twin[J]. Nuclear Power Engineering, 2021, 42(S2): 48-53. doi: 10.13832/j.jnpe.2021.S2.0048

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Study on a Data-Enabled Physics-Informed Reactor Physics Operational Digital Twin

doi: 10.13832/j.jnpe.2021.S2.0048

Gong Helin^1
,,
Chen Zhang¹,
Li Qing^{1
,
,},
Cheng Sibo²

1.
Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu, 610213, China
2.
Data Science Institute, Department of Computing, Imperial College London, London, SW7 2AZ, UK

Received Date: 2021-07-19
Accepted Date: 2021-12-06
Rev Recd Date: 2021-09-26
Publish Date: 2021-12-29

Abstract

Abstract

To realize the fast and accurate online calculation and to predict the operation behavior of nuclear reactors, a physics-informed data-enabled reactor physics operational digital twin is proposed, to achieve rapid and accurate calculation of physical fields such as fast and thermal neutron flux and power distribution in the core. The physics-informed property is achieved through a fast calculation model of neutronics based on model order reduction technology and machine learning; the data enabled property is realized through an inverse model based on the fast calculation model. The test of the design and operation data of HPR1000 reactor shows that the digital twin meets the engineering requirements in terms of time and accuracy, and has the potential for online monitoring applications in real engineering.
- Digital twin,
- Model order reduction,
- Machine learning,
- Proper Orthogonal Decomposition (POD),
- Nuclear reactor physics

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References

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