Application of the Relative Power Contribution Methodology to the Analysis of a Control System Failure

2009 ◽  
Author(s):  
Rogelio Castillo-Dura´n ◽  
Javier Ortiz-Villafuerte ◽  
Rodolfo Amador-Garci´a ◽  
Edmundo del-Valle-Gallegos ◽  
Javier C. Palacios-Herna´ndez ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Flow Behavior ◽  
Reactor Power ◽  
Relative Power ◽  
Transient Event ◽  
Time Frequency ◽  
The Core ◽  
Power Spectral ◽  
Flow Through ◽  
Short Time

The Relative Power Contribution methodology has been applied to delineate the initiating event leading to a BWR transient. Diverse reactor signals were analyzed to calculate the coefficients required on the relative power contribution method. Those coefficients were computed from an autoregressive multivariable model. Among the signals used in the analysis of the transient event are total flow through the core, pressure drop across the core, feedwater flow, and reactor power. Analyses of the same type of transient event showed a resonance of the main event frequency on the range within which it has been considered and observed frequencies related to some failures of certain control systems of a nuclear power plant. Those analyses employed the short-time Fourier transform or the power spectral density, for time-frequency and frequency-only domains, respectively. In this work, the same value of the frequency of the resonance mentioned above was obtained through the relative power contribution analysis, but, furthermore it was found that the feedwater flow behavior had an important impact on the transient event, and also that the transient event was not initiated by a reactivity-related instability.

New Human-Machine Interface at VR-1 Training Reactor

2010 ◽  
Author(s):  
Martin Kropi´k ◽  
Jan Rataj ◽  
Monika Jurˇicˇkova´
Keyword(s):  
User Interface ◽  
Foreign Students ◽  
Nuclear Power ◽  
English Language ◽  
Reactor Power ◽  
Text Messages ◽  
Reactor Operation ◽  
The Core ◽  
Machine Interface ◽  
And Training

The paper describes a new human-machine (HMI) interface of the VR-1 nuclear training reactor at the Czech Technical University in Prague. The VR-1 reactor is primarily used for training of university students and future nuclear power plant staff. The new HMI was designed to meet functional, ergonomic and aesthetic requirements. It contains a PC with two monitors. The first alphanumerical monitor presents text messages about the reactor operation and status; next, the operator can enter commands to control the reactor operation. The second graphical monitor provides parameters of reactor operation and shows the course of the reactor power and other parameters. Furthermore, it is able to display the core configuration, perform reactivity calculations, etc. The HMI is also equipped with an alarm annunciator. Due to a high number of foreign students and visitors at the reactor, the Czech and English language versions of the user interface are available. The HMI contains also a History server which provides a very detailed storage and future presentation of the reactor operation. The new HMI improves safety and comfort of the reactor utilization, facilitates experiments and training, and provides better support for foreign visitors.

Autoregressive Multivariate Analysis of BWR Bistable Flow

2008 ◽  
Author(s):  
Rogelio Castillo-Dura´n ◽  
Javier Ortiz-Villafuerte ◽  
Raymundo Go´mez-Herrera ◽  
Gabriel Calleros-Micheland
Keyword(s):  
Signal Analysis ◽  
Nuclear Power ◽  
Safety Concern ◽  
Reactor Power ◽  
Relative Power ◽  
Recirculation Flow ◽  
Operation Conditions ◽  
Cause Of Failure ◽  
Flow Oscillations ◽  
Stable Flow

Bi-stable flow patterns can induce flow oscillations possibly leading to power fluctuations. In other cases, bi-stable flow can generate loads on components, so that structural stresses may become a potential cause of failure. This type of flow occurs in BWRs at different operation conditions, so there is no an absolute methodology for detection and prediction of such phenomenon. In this work, a multivariate autoregressive (MAR) analysis is performed to different signals related to a bi-stable flow event that occurred in one of the BWR Units at the Laguna Verde Nuclear Power Plant. The signal analysis was performed with the home-developed NOISE computer program, which, among several other applications, computes the autoregressive coefficients which contain the information of the dynamics of the signal, and that later are used to determine the relative power contribution (RPC) ratio, which in turn allows establishing the influence of the different signals on each other. From the signal analysis, among the important results obtained, it was found that no new frequencies appeared during the event. Also, it was determined through the Relative Power Contribution ratios that the most probable cause of reactor power change was the flow variation in the recirculation flow of loop B. Maximum variations (both above and below) from the initial average reactor power were 0.5%, so the bi-stable flow impact was of no safety concern.

scholarly journals Direct Numerical Simulation of the Flow Through a Randomly Packed Pebble Bed

2020 ◽  
Vol 142 (4) ◽  
Author(s):  
Mustafa Alper Yildiz ◽  
Gerrit Botha ◽  
Haomin Yuan ◽  
Elia Merzari ◽  
Richard C. Kurwitz ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Direct Numerical Simulation ◽  
Power Systems ◽  
Nuclear Power ◽  
Flow Behavior ◽  
Reactor Core ◽  
Reynolds Numbers ◽  
Fourth Generation ◽  
Flow Through ◽  
Flow Domain

Abstract The proposition for molten salt and high-temperature gas-cooled reactors has increased the focus on the dynamics and physics in randomly packed pebble beds. Research is being conducted on the validity of these designs as a possible contestant for the fourth-generation nuclear power systems. A detailed understanding of the coolant flow behavior is required in order to ensure proper cooling of the reactor core during normal and accident conditions. In order to increase the understanding of the flow through these complex geometries and enhance the accuracy of lower-fidelity modeling, high-fidelity approaches such as direct numerical simulation (DNS) can be utilized. Nek5000, a spectral-element computational fluid dynamics (CFD) code, was used to develop DNS fluid flow data. The flow domain consisted of 147 pebbles enclosed by a bounding wall. In the work presented, the Reynolds numbers ranged from 430 to 1050 based on the pebble diameter and inlet velocity. Characteristics of the flow domain such as volume averaged porosity, axial porosity, and radial porosity were studied and compared with correlations available in the literature. Friction factors from the DNS results for all Reynolds numbers were compared with correlations in the literature. The first- and second-order statistics show good agreement with the available experimental data. Turbulence length scales were analyzed in the flow. Reynolds stress anisotropy was characterized by utilizing invariant analysis. Overall, the results of the analysis in this study provide deeper understanding of the flow behavior and the effect of the wall in packed beds.

Dynamic Diagnosis of Elastic Coupling Transmissions of Technological Equipments Based on Joint Time-Frequency Evaluations

2014 ◽  
Vol 657 ◽  
pp. 465-469
Author(s):  
Silviu Năstac ◽  
Carmen Debeleac ◽  
Cristian Simionescu
Keyword(s):  
Spectral Composition ◽  
Experimental Tests ◽  
Time Domain Analysis ◽  
Time Frequency ◽  
Power Spectral ◽  
The Time Domain ◽  
Behaviour Changes ◽  
Short Time ◽  
Dynamic Diagnosis

This work presents a practical solution intended for dynamic diagnosis of the technical systems based on a set of computational methods for processing and analyzing of the acquired signals. This ensemble of methods leads to the joint time-frequency evaluations and assures a multiple way to estimate the potential damages of certain parts of the tested system. Short-Time-Fourier-Transformation, Cepstrum analysis, power spectral density estimate, together with a group of stochastic estimators composes the structured procedure for dynamic diagnosis. The proposed approach of dynamic diagnosis combines the advantages of the time domain analysis, such as the simplicity and the possibility of parameters investigation during their time evolution, with the power of spectral complex evaluations, sustained by the distribution and shifting trend of spectrum. Hereby it has provided a suitable tool for characterization of spectral composition changes in time during the entire experimental tests. This information is able to reveal the dynamic behaviour changes of supervised parts, components or entire system.

Time Frequency Analysis of Femoral Doppler Ultrasound Signals by AR Modelling

2013 ◽  
Vol 302 ◽  
pp. 319-325
Author(s):  
Latfaoui Mahieddine ◽  
Bereksi Reguig Fethi
Keyword(s):  
Moving Average ◽  
Frequency Resolution ◽  
Doppler Spectrum ◽  
Autoregressive Moving Average ◽  
Ultrasonic Signals ◽  
Time Frequency ◽  
Power Spectral ◽  
Doppler Signals ◽  
Short Time ◽  
The Impact

In this study, we have compared the efficiency of the short time Fourier transform (STFT) and autoregressive modelling (AR) and autoregressive moving average (ARMA) of the femoral Doppler artery ultrasonic signals, in order to determine the spectral broadening index (SBI). Our aim is to detect the impact of the two modelling approaches on sonograms and of power spectral density- frequency diagrams obtained from femoral arterial Doppler Signals. The sonograms have been then used to compare the methods in terms of their frequency resolution and effects in determining the stenosis of femoral artery. In this paper we have used generated frequency envelopes from the Doppler spectrum to determine an index showing the degree of severity of stenosis cases. This index called broadening spectral index is calculated for various real cases.

scholarly journals Strain Sensitivity Enhancement of Broadband Ultrasonic Signals in Plates Using Spectral Phase Filtering

2021 ◽  
Vol 11 (6) ◽  
pp. 2582
Author(s):  
Lucas M. Martinho ◽  
Alan C. Kubrusly ◽  
Nicolás Pérez ◽  
Jean Pierre von der Weid
Keyword(s):  
Fourier Transform ◽  
Guided Waves ◽  
Strain Level ◽  
Energy Concentration ◽  
Short Time Fourier Transform ◽  
Time Frequency ◽  
Frequency Representation ◽  
The Fourier Transform ◽  
Short Time ◽  
Sensitivity Gain

The focused signal obtained by the time-reversal or the cross-correlation techniques of ultrasonic guided waves in plates changes when the medium is subject to strain, which can be used to monitor the medium strain level. In this paper, the sensitivity to strain of cross-correlated signals is enhanced by a post-processing filtering procedure aiming to preserve only strain-sensitive spectrum components. Two different strategies were adopted, based on the phase of either the Fourier transform or the short-time Fourier transform. Both use prior knowledge of the system impulse response at some strain level. The technique was evaluated in an aluminum plate, effectively providing up to twice higher sensitivity to strain. The sensitivity increase depends on a phase threshold parameter used in the filtering process. Its performance was assessed based on the sensitivity gain, the loss of energy concentration capability, and the value of the foreknown strain. Signals synthesized with the time–frequency representation, through the short-time Fourier transform, provided a better tradeoff between sensitivity gain and loss of energy concentration.

scholarly journals Deep Learning Approach for Vibration Signals Applications

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3929
Author(s):  
Han-Yun Chen ◽  
Ching-Hung Lee
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Parameters Optimization ◽  
Frequency Spectra ◽  
Vibration Signals ◽  
Bearing Faults ◽  
Time Frequency ◽  
And Performance ◽  
The One ◽  
Short Time

This study discusses convolutional neural networks (CNNs) for vibration signals analysis, including applications in machining surface roughness estimation, bearing faults diagnosis, and tool wear detection. The one-dimensional CNNs (1DCNN) and two-dimensional CNNs (2DCNN) are applied for regression and classification applications using different types of inputs, e.g., raw signals, and time-frequency spectra images by short time Fourier transform. In the application of regression and the estimation of machining surface roughness, the 1DCNN is utilized and the corresponding CNN structure (hyper parameters) optimization is proposed by using uniform experimental design (UED), neural network, multiple regression, and particle swarm optimization. It demonstrates the effectiveness of the proposed approach to obtain a structure with better performance. In applications of classification, bearing faults and tool wear classification are carried out by vibration signals analysis and CNN. Finally, the experimental results are shown to demonstrate the effectiveness and performance of our approach.

scholarly journals Noise power spectral density scaled SNR response estimation with restricted range search for sound source localisation using unmanned aerial vehicles

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Benjamin Yen ◽  
Yusuke Hioka
Keyword(s):  
Spectral Density ◽  
Noise Reduction ◽  
Power Spectral Density ◽  
Sound Source ◽  
Processing Algorithm ◽  
Post Processing ◽  
Time Frequency ◽  
Distance Error ◽  
Rotor Noise ◽  
Power Spectral

Abstract A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.

Upward Vertical Two-Phase Flow Through an Annulus—Part II: Modeling Bubble, Slug, and Annular Flow

1992 ◽  
Vol 114 (1) ◽  
pp. 14-30 ◽  
Author(s):  
E. F. Caetano ◽  
O. Shoham ◽  
J. P. Brill
Keyword(s):  
Flow Pattern ◽  
Annular Flow ◽  
Two Phase Flow ◽  
Flow Behavior ◽  
Bubble Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Through ◽  
Physical Phenomena ◽  
Good Agreement

Mechanistic models have been developed for each of the existing two-phase flow patterns in an annulus, namely bubble flow, dispersed bubble flow, slug flow, and annular flow. These models are based on two-phase flow physical phenomena and incorporate annulus characteristics such as casing and tubing diameters and degree of eccentricity. The models also apply the new predictive means for friction factor and Taylor bubble rise velocity presented in Part I. Given a set of flow conditions, the existing flow pattern in the system can be predicted. The developed models are applied next for predicting the flow behavior, including the average volumetric liquid holdup and the average total pressure gradient for the existing flow pattern. In general, good agreement was observed between the experimental data and model predictions.

scholarly journals Ultrasonic Assessment of Thickness and Bonding Quality of Coating Layer Based on Short-Time Fourier Transform and Convolutional Neural Networks

Coatings ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 909
Author(s):  
Azamatjon Kakhramon ugli Malikov ◽  
Younho Cho ◽  
Young H. Kim ◽  
Jeongnam Kim ◽  
Junpil Park ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Coating Layer ◽  
Ultrasonic Pulse ◽  
Short Time Fourier Transform ◽  
Coating Materials ◽  
Time Frequency ◽  
High Attenuation ◽  
Bonding State ◽  
The Time Domain ◽  
Short Time

Ultrasonic non-destructive analysis is a promising and effective method for the inspection of protective coating materials. Offshore coating exhibits a high attenuation rate of ultrasonic energy due to the absorption and ultrasonic pulse echo testing becomes difficult due to the small amplitude of the second echo from the back wall of the coating layer. In order to address these problems, an advanced ultrasonic signal analysis has been proposed. An ultrasonic delay line was applied due to the high attenuation of the coating layer. A short-time Fourier transform (STFT) of the waveform was implemented to measure the thickness and state of bonding of coating materials. The thickness of the coating material was estimated by the projection of the STFT into the time-domain. The bonding and debonding of the coating layers were distinguished using the ratio of the STFT magnitude peaks of the two subsequent wave echoes. In addition, the advantage of the STFT-based approach is that it can accurately and quickly estimate the time of flight (TOF) of a signal even at low signal-to-noise ratios. Finally, a convolutional neural network (CNN) was applied to automatically determine the bonding state of the coatings. The time–frequency representation of the waveform was used as the input to the CNN. The experimental results demonstrated that the proposed method automatically determines the bonding state of the coatings with high accuracy. The present approach is more efficient compared to the method of estimating bonding state using attenuation.

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