Application of Continuous and Structural ARMA modeling for noise analysis of a BWR coupled core and plant instability event

Demeshko, Marina; Dokhane, A.; Washio, Takashi; Ferroukhi, H.; Kawahara, Yoshinobu; Aguirre, C.

doi:10.1016/j.anucene.2014.08.045

Cited by 5 publications

(4 citation statements)

References 19 publications

(35 reference statements)

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“…While the current analysis justi es, with greater condence, the conclusion made in Ref. 21, it could additionally, with the help of connectivity analysis, identify precisely the real source of perturbation, i.e., TCV A .…”

Section: A High Decay Ratio During Start-up Of Kkl Cycle 24mentioning

confidence: 64%

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Application of causality analysis on nuclear reactor systems

Chionis

Dokhane

Ferroukhi

et al. 2019

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Causality analysis is a substantial tool for identifying cause-and-e ect links between di erent components of a system and has been extensively used in various areas of science such as neuroscience, climatology, and econometrics. This analysis is carried out in terms of the renormalized partial directed coherence and the directed transfer function connectivity measures. Applying such analysis in the nuclear reactor eld is of paramount importance since it can help in inferring cause-and-e ect relationships between highly coupled processes, and consequently, it can assist on the safe and reliable operation of a nuclear power plant during the occurrence of possible disturbances or malfunctions. The e ectiveness of the connectivity analysis is demonstrated through several simulated and measured test cases. Results show that the connectivity analysis is able to identify accurately the importance and central role of the activation signal when it is applied on a simple analytical model and a simulated nuclear reactor system. In addition, the application on more realistic and complex measured data sets of a Swiss boiling water reactor illustrates the capability of this analysis to indicate possible causes behind the observed anomalies or trends observed at certain conditions and, more importantly, allows a better understanding of the underlying interactions among di erent neutronic and thermal-hydraulic processes.

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Section: A High Decay Ratio During Start-up Of Kkl Cycle 24mentioning

confidence: 64%

“…It should be noted that, in Ref. 21 it was shown that the stability event was originated from a disturbance related to the steam lines. While the current analysis justi es, with greater condence, the conclusion made in Ref.…”

Section: A High Decay Ratio During Start-up Of Kkl Cycle 24mentioning

confidence: 99%

Application of causality analysis on nuclear reactor systems

Chionis

Dokhane

Ferroukhi

et al. 2019

Chaos: An Interdisciplinary Journal of Nonlinear Science

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Discussion and Remarksmentioning

confidence: 99%

Non-Linear Stability Analysis of Real Signals from Nuclear Power Plants (Boiling Water Reactors) based on Noise Assisted Empirical Mode Decomposition Variants and the Shannon Entropy

Olvera-Guerrero¹,

Prieto‐Guerrero²,

Espinosa-Paredes³

2017

Preprint

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“…The mechanism of density wave oscillations for two-phase flow has recently received great attention, remaining as an important issue of scientific and technological interest (e.g., [40,[42][43][44][45][46][47][48]. However, the core stability is due to fluctuations in coolant flow and power generation process coupled via nuclear feedback where the non-linear nature has been a challenge for the development of stability monitors.…”

Section: Discussion and Remarksmentioning

confidence: 99%

Non-Linear Stability Analysis of Real Signals from Nuclear Power Plants (Boiling Water Reactors) Based on Noise Assisted Empirical Mode Decomposition Variants and the Shannon Entropy

Olvera-Guerrero

Prieto‐Guerrero

Espinosa-Paredes

2017

Entropy

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There are currently around 78 nuclear power plants (NPPs) in the world based on Boiling Water Reactors (BWRs). The current parameter to assess BWR instability issues is the linear Decay Ratio (DR). However, it is well known that BWRs are complex non-linear dynamical systems that may even exhibit chaotic dynamics that normally preclude the use of the DR when the BWR is working at a specific operating point during instability. In this work a novel methodology based on an adaptive Shannon Entropy estimator and on Noise Assisted Empirical Mode Decomposition variants is presented. This methodology was developed for real-time implementation of a stability monitor. This methodology was applied to a set of signals stemming from several NPPs reactors (Ringhals-Sweden, Forsmark-Sweden and Laguna Verde-Mexico) under commercial operating conditions, that experienced instabilities events, each one of a different nature.Entropy 2017, 19, 359 2 of 33 operates at a low mass flow and at high nominal power. Another current trend is to increase the size of the core, which causes a weaker special coupling in the neutron field which increases the susceptibility of the reactor to experiencing unstable oscillations. In summary, all current tendencies related to reactor design enhance the regions where the reactor should not be operated (reactor operation at low flow and high power).Also, the DR often jumps discontinuously from the well stable to the far-unstable region [7]. The BWR stability is of primary interest from the point of view of BWR operation, due to the fact, that the stability margin may be strongly reduced during plant maneuvering and transients [8]. According to these issues, the DR might not be a reliable monitoring index after all, under certain operating conditions. Besides, in regular operating conditions, the need for stationary signals might be a handicap for DR estimation. Thus, it is relevant to explore new alternative methodologies and indexes adapted to accommodate for non-stationary and non-linear BWR signal behavior.In [9] a short time Fourier transform based technique was explored to study the time dependence of the natural frequency when the BWR signal is non-stationary. Later, the wavelet theory was applied to explore new alternatives for transient instability analysis [10,11]. However, in general BWR signals are non-stationary and non-linear, thus Fourier-based or wavelet-based approaches might lead to a biased stability analysis. Several methods for non-linear BWR stability analysis have been applied before [12,13], to study BWR signals containing stationary and non-stationary segments. In this work, the Shannon Entropy (SE) was applied, to infer whether it can be used as a novel stability parameter for BWRs. The SE is a concept that was developed by Claude E. Shannon [14] to study a discrete source through the information content of this source. The SE is a statistical index that quantifies the complexity of a signal. In this case, the BWR stability issue is assessed quantifying the complexity of BWR si...

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Application of Continuous and Structural ARMA modeling for noise analysis of a BWR coupled core and plant instability event

Cited by 5 publications

References 19 publications

Application of causality analysis on nuclear reactor systems

Application of causality analysis on nuclear reactor systems

Non-Linear Stability Analysis of Real Signals from Nuclear Power Plants (Boiling Water Reactors) based on Noise Assisted Empirical Mode Decomposition Variants and the Shannon Entropy

Non-Linear Stability Analysis of Real Signals from Nuclear Power Plants (Boiling Water Reactors) Based on Noise Assisted Empirical Mode Decomposition Variants and the Shannon Entropy

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