State estimation of external neutron source driven sub-critical core using adaptive Kalman filter

Li, Wenhuai; Qiu, Ruoxiang; Cai, Jiejin; Ding, Peng; Duan, Chengjie; Cui, Dawei; Shi, Xiuan; Lin, Jiming; Shu, Chen

doi:10.1016/j.anucene.2020.107313

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…For example, temperature limits for fuel rods or fuel cladding are vital to avoid material performance failure. On the other hand, these unmeasurable state variables can only be derived from mathematical models based on the measured values [4] . The accuracy of the model and the uncertainty of the measured data have a great influence on the estimation or precision control of these unmeasured variables.…”

Section: Probabilistic Monitoringmentioning

confidence: 99%

Research on the Multi-probability of a Nuclear Reactor Core Digital Twins in the HeTu platform

Li,

Cai,

et al. 2023

J. Phys.: Conf. Ser.

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Digital twin (DT) technology plays a fundamental role in innovation in the energy field. At present, research of nuclear reactor DT is mainly focused on methodologies of multi-disciplinary, multi-physical, and multi-scale coupling simulation. However, the lack of research on multi-probability seems to limit the DT application. Multi-probabilities are widely found in reactor operation, such as process measurement uncertainty, equipment degradation uncertainty, theoretical model uncertainty, and so on. How to realize the DT of the reactor system based on the multi-probability principle to achieve the real-time operation state and the remaining useful life estimation, and to realize the autonomous operation control under the uncertainties, are the current hotspot and difficult issues. The solutions of a reactor core DT platform HeTu are discussed in this paper for probability estimation and probability control based on probability programming methodologies. The results show that Bayesian estimation and model prediction control methods proposed in HeTu could obtain satisfactory results for practical application.

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Section: Probabilistic Monitoringmentioning

confidence: 99%