Decay Ratio estimation in BWRs based on the improved complete ensemble empirical mode decomposition with adaptive noise

Olvera-Guerrero, Omar Alejandro; Prieto‐Guerrero, Alfonso; Espinosa-Paredes, Gilberto

doi:10.1016/j.anucene.2016.12.035

Cited by 23 publications

(22 citation statements)

References 16 publications

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“…Also, in this same figure, a DR estimate of the segments is shown to illustrate the performance of the SE over the DR to analyze the stability of the studied signal. The DR was estimated in the same way as in [25]. We have established empirical stability thresholds based on our numerical experiments for the SE (Although more experiments are needed in this direction to accurately confirm this finding, but such studies leave the scope of this work).…”

Section: Aprm Signal From the Forsmark Benchmarkmentioning

confidence: 80%

“…The validation of the methodology presented in this paper is performed doing experiments with real signals taken from the Forsmark and Ringhals stability benchmarks and from a Laguna Verde instability event and presented in Section 6. Also in this same section, the SE results are compared with current DR estimations, computed via techniques based on default EMD [24,25]. Our major findings regarding our novel methodology are talked through in Section 7.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

“…Such issue might spoil the meaning of individual IMFs and thus, thwart any default EMD signal analysis methodology. For further details about the impact of the mode mixing problem in BWR signals, please refer to [25]. Thus, the methods that are discussed in the following sections to mitigate the mode mixing issue, add an ensemble of realizations of white noise to the signal of interest (hence, the name noise assisted method is used to define improved variations of EMD), to repair and exploit this dyadic filter bank property of the EMD, to improve IMF acquisition of the signal of interest x.…”

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confidence: 99%

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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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Section: Aprm Signal From the Forsmark Benchmarkmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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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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Section: Introductionmentioning

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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Resolving mode mixing in boiling water reactors instability analysis using variational mode decomposition

Montalvo

Gavilan

Garcı́a-Berrocal

et al. 2020

Intl J of Energy Research

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In dynamic, complex and nonlinear systems, the analysis of transients, instabilities or unusual events is fundamental, as well as the knowledge of the system's behavior in the frequency space. What is usual in this type of study is to have discrete and digitally acquired data, due to a sampling process with a determined period or frequency. Extracting information from this data set is done by numerical methods, such as the Fourier Transform (FFT), the Hilbert-Huang Transform (HHT) or techniques from chaos mathematics (Attractors). In this way we have scarce data, with some loss of information, analyzed with numerical techniques that introduce, also, some dilution of the information. In particular, the techniques of analysis in the frequency space, by their very nature, blur, frequencies and bandwidths. This leads in some cases to the identification of unsuitable or very wide frequencies or intervals, which make the extracted information unusable. To this effect, we have studied the VMD technique that provides more real and representative frequencies of the system as well as narrower bandwidths that make possible better identification of phenomena and influences. This technique has been applied to the analysis of thermohydraulic instabilities in nuclear boiling water reactors (BWR). The cases had already been analyzed with STFT and HHT techniques. The results of the application of the VMD shows that the mode mixing is solved, so modes obtained are monofrequency and these frequency bands are narrower than in previous methodologies. This improved performance allows using backbone plots for identifying which modes are excited in instabilities events.

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Decay Ratio estimation in BWRs based on the improved complete ensemble empirical mode decomposition with adaptive noise

Cited by 23 publications

References 16 publications

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

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

Resolving mode mixing in boiling water reactors instability analysis using variational mode decomposition

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