scholarly journals A Novel Assessment of Delayed Neutron Detector Data in CANDU Reactors

2020 ◽  
Vol 6 (4) ◽  
Author(s):  
Will Aylward ◽  
Christopher Wallace ◽  
Graeme West ◽  
Curtis McEwan
Keyword(s):  
Nuclear Power ◽  
Best Practice ◽  
Machine Learning Algorithms ◽  
Delayed Neutron ◽  
Defect Identification ◽  
Financial Investment ◽  
Candu Reactors ◽  
Initial Batch ◽  
Unseen Data ◽  
Defects Identification

Abstract A common opportunity for nuclear power plant operators is ensuring that routinely collected data are fully leveraged. Exploiting data analytics can enable improvements in anomaly detection and condition monitoring by identifying previously unseen data trends and correlations without major financial investment. One such opportunity is in facilitating the detection of fuel defects by augmenting the delayed neutron (DN) monitoring system deployed in the majority of Canada deuterium uranium (CANDU) reactors. In this paper, we demonstrate using archive data that the detection of fuel defects can be accelerated using this system in combination with the use of a deeper historical dataset and the introduction of a smoothing algorithm. The current defect identification process relies on the analysis of data of high variance and is subject to the judgment of a domain expert, resulting in variable defect identification periods. The proposed approaches seek to mitigate this and alleviate the variable identification time. Initial results presented here show that for an initial batch of 30 defects, identification periods can be meaningfully reduced compared to the current process, with defects potentially visible on an average of 11.4 days earlier. By shortening this identification period, fuel containing defects can be scheduled for earlier removal, reducing the risk of statutory shutdown obligations, protecting personnel, and promoting industry best practice. Exploring a historical dataset identifies previously undocumented trends and we discuss the potential to produce correlations with other reactor parameters. The application of this knowledge can lead to opportunities in the use of machine learning algorithms and, ultimately, more accurate predictions.

scholarly journals A Comparative Survey of Feature Extraction and Machine Learning Methods in Diverse Acoustic Environments

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1274
Author(s):  
Daniel Bonet-Solà ◽  
Rosa Ma Alsina-Pagès
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Best Practice ◽  
Nearest Neighbor ◽  
Gaussian Mixture ◽  
Machine Learning Algorithms ◽  
Multimedia Retrieval ◽  
Natural Environments ◽  
K Nearest Neighbor ◽  
Acoustic Environments

Acoustic event detection and analysis has been widely developed in the last few years for its valuable application in monitoring elderly or dependant people, for surveillance issues, for multimedia retrieval, or even for biodiversity metrics in natural environments. For this purpose, sound source identification is a key issue to give a smart technological answer to all the aforementioned applications. Diverse types of sounds and variate environments, together with a number of challenges in terms of application, widen the choice of artificial intelligence algorithm proposal. This paper presents a comparative study on combining several feature extraction algorithms (Mel Frequency Cepstrum Coefficients (MFCC), Gammatone Cepstrum Coefficients (GTCC), and Narrow Band (NB)) with a group of machine learning algorithms (k-Nearest Neighbor (kNN), Neural Networks (NN), and Gaussian Mixture Model (GMM)), tested over five different acoustic environments. This work has the goal of detailing a best practice method and evaluate the reliability of this general-purpose algorithm for all the classes. Preliminary results show that most of the combinations of feature extraction and machine learning present acceptable results in most of the described corpora. Nevertheless, there is a combination that outperforms the others: the use of GTCC together with kNN, and its results are further analyzed for all the corpora.

Automatic defect identification on PWR nuclear power station fuel pellets

2012 ◽  
Vol 245 ◽  
pp. 62-77 ◽  
Author(s):  
Adriano Fortunato de Oliveira ◽  
Antônio Carlos de Abreu Mól ◽  
Celso Marcelo Franklin Lapa ◽  
Victor Gonçalves Gloria Freitas ◽  
Cláudio Marcio do N. de A. Pereira ◽  
...  
Keyword(s):  
Nuclear Power Station ◽  
Nuclear Power ◽  
Power Station ◽  
Defect Identification ◽  
Fuel Pellets ◽  
Station Fuel ◽  
Power Station Fuel

scholarly journals What happens when the nuclear power plant goes? Social and economic consequences of dismantling for the site and its population

2021 ◽  
Vol 1 ◽  
pp. 265-266
Author(s):  
Caroline Kramer
Keyword(s):  
Nuclear Power ◽  
Best Practice ◽  
Operating Time ◽  
Rapid Change ◽  
Intention To Leave ◽  
Economic Consequences ◽  
Power Station ◽  
Individual Level ◽  
Social Scientific ◽  
The Individual

Abstract. This project deals with the question of what the overall social and economic consequences of dismantling a nuclear power station are for the population and the site. Various disciplines and specialist fields are concerned with questions that touch on the topic of dismantling nuclear technical facilities; however, there are so far no research projects that examined these processes from social scientific, geographic and engineering scientific perspectives. This article concentrates predominantly on the former perspective of the dismantling. Within the framework of this project the affected population and experts from the communities were asked how they deal with the dismantling of the nuclear power stations, which were triggered by the rapid change in energy policy following the accident in Fukushima in 2011. It became clear that there were various strategies for dealing with this process depending on the location. This was the reason to follow up the question of coping with this process at different locations. It could be shown, for example, that the consequences of this event were essentially determined by how the community was already positioned beforehand, e.g. whether the economic situation was a monostructure or whether long-term considerations about the future had already been made during the operating time of the power station. At the individual level, the “prerequisites” in the sense of individual value orientation and the spatially related identity, were also essentially responsible for how the risks of the dismantling and the further development of the community were perceived and evaluated. Furthermore, it was compiled from where the people extracted their information, which sources had a high or low credibility, which worries they have with respect to the near future and whether they have the intention to leave the community. In this project it became clear that there were examples of best practice with respect to dealing with this rapid and fundamental change at the locations.

Investigation on Header Manifold Model Effect at CANDU6 Large Loss of Cooling Accident

2008 ◽  
Author(s):  
Daniel Dupleac ◽  
Ilie Prisecaru ◽  
Mirea Mladin ◽  
Gheorghe Negut ◽  
Petre Ghitescu
Keyword(s):  
Nuclear Power ◽  
Flow Distribution ◽  
Strong Impact ◽  
Pressure Gradients ◽  
Axial Pressure ◽  
Nuclear Power Reactor ◽  
Pressure Drops ◽  
Candu Reactors ◽  
Loss Of Coolant Accident ◽  
Pressure Tubes

In a CANDU 6 nuclear power reactor fuel bundles are supported in horizontal Zircaloy pressure tubes tube through which the heavy-water coolant flows. 95 pressure tubes are connected by individual feeders to a common header. For CANDU 6 safety analyses, even when multiple channels model is employed, only one node is used for header. In this approach, all the channels are subjected to the same boundary condition. However, site inlet and outlet header pressure measurements and ultrasonic feeder flow data, confirm the existence of axial pressure gradients along the inlet and outlet headers. These axial pressure gradients would give rise to individual header-to-header pressure drops for each channel and also to flow distribution throughout both the inlet and outlet headers. In this paper, the header manifold model effect on the large break loss of coolant accident analyses of CANDU reactors has been performed by RELAP5/ mod 3.4 code. The 35% reactor inlet header break was selected for this study, as this break size produce the highest fuel clad temperature among all postulated breaks size. The results obtained considering the header manifold model, show that location of fuel channel upon break location has a strong impact on peak clad temperature calculation.

Centralization of Canada’s Spent Nuclear Fuel

2013 ◽  
Author(s):  
Krista Nicholson ◽  
John McDonald ◽  
Shona Draper ◽  
Brian M. Ikeda ◽  
Igor Pioro
Keyword(s):  
Nuclear Fuel ◽  
Site Selection ◽  
Nuclear Power ◽  
Power Plants ◽  
Spent Nuclear Fuel ◽  
Selection Process ◽  
Spent Fuel ◽  
Geologic Repository ◽  
Candu Reactors ◽  
High Level

Currently in Canada, spent fuel produced from Nuclear Power Plants (NPPs) is in the interim storage all across the country. It is Canada’s long-term strategy to have a national geologic repository for the disposal of spent nuclear fuel for CANada Deuterium Uranium (CANDU) reactors. The initial problem is to identify a means to centralize Canada’s spent nuclear fuel. The objective of this paper is to present a solution for the transportation issues that surround centralizing the waste. This paper reviews three major components of managing and the transporting of high-level nuclear waste: 1) site selection, 2) containment and 3) the proposed transportation method. The site has been selected based upon several factors including proximity to railways and highways. These factors play an important role in the site-selection process since the location must be accessible and ideally to be far from communities. For the containment of the spent fuel during transportation, a copper-shell container with a steel structural infrastructure was selected based on good thermal, structural, and corrosion resistance properties has been designed. Rail has been selected as the method of transporting the container due to both the potential to accommodate several containers at once and the extensive railway system in Canada.

scholarly journals Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant

2017 ◽  
Author(s):  
Donald D. Lucas ◽  
Matthew D. Simpson ◽  
Philip Cameron-Smith ◽  
Ronald L. Baskett
Keyword(s):  
Machine Learning ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Inverse Modeling ◽  
Land Surface ◽  
Nuclear Power ◽  
Learning Algorithms ◽  
Distribution Functions ◽  
Machine Learning Algorithms ◽  
Surface Model

Abstract. Probability distribution functions (PDFs) of model inputs that affect the transport and dispersion of a trace gas released from a coastal California nuclear power plant are quantified using ensemble simulations, machine learning algorithms, and Bayesian inversion. The PDFs are constrained by observations of tracer concentrations and account for uncertainty in meteorology, transport, diffusion, and emissions. Meteorological uncertainty is calculated using an ensemble of simulations of the Weather Research and Forecasting (WRF) model that samples five categories of model inputs (initialization time, boundary layer physics, land surface model, nudging options, and reanalysis data). The WRF output is used to drive tens of thousands of FLEXPART dispersion simulations that sample a uniform distribution of six emissions inputs. Machine learning algorithms are trained on the ensemble data, and used to quantify the sources of ensemble variability and to infer, via inverse modeling, the values of the 11 model inputs most consistent with tracer measurements. We find a substantial ensemble spread in tracer concentrations (factors of 10 to 103), most of which is due to changing emissions inputs (about 80 %), though the cumulative effects of meteorological variations are not negligible. The performance of the inverse method is verified using synthetic observations generated from arbitrarily selected simulations. When applied to measurements from a controlled tracer release experiment, the most likely inversion results are within about 200 meters of the known release location, 5 and 50 minutes of the release start and duration times, respectively, and 22 % of the release amount. The inversion also estimates probabilities of different combinations of WRF inputs of matching the tracer observations.

scholarly journals Implications for Deriving Regional Fossil Fuel CO2 Estimates from Atmospheric Observations in a Hot Spot of Nuclear Power Plant 14CO2 Emissions

Radiocarbon ◽  
2013 ◽  
Vol 55 (3) ◽  
pp. 1556-1572 ◽  
Author(s):  
Felix R Vogel ◽  
Ingeborg Levin ◽  
Doug E J Worthy
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Fossil Fuels ◽  
Hot Spot ◽  
Nuclear Industry ◽  
Local Concentration ◽  
Candu Reactors ◽  
Global Emission ◽  
Observational Site ◽  
Pseudo Data

Using Δ14C observations to infer the local concentration excess of CO2 due to the burning of fossil fuels (ΔFFCO2) is a promising technique to monitor anthropogenic CO2 emissions. A recent study showed that 14CO2 emissions from the nuclear industry can significantly alter the local atmospheric 14CO2 concentration and thus mask the Δ14C depletion due to ΔFFCO2. In this study, we investigate the relevance of this effect for the vicinity of Toronto, Canada, a hot spot of anthropogenic 14CO2 emissions. Comparing the measured emissions from local power plants to a global emission inventory highlighted significant deviations on interannual timescales. Although the previously assumed emission factor of 1.6 TBq(GWa)-1 agrees with the observed long-term average for all CANDU reactors of 1.50 ± 0.18 TBq(GWa)-1. This power-based parameterization neglects the different emission ratios for individual reactors, which range from 3.4 ± 0.82 to 0.65 ± 0.09 TBq(GWa)-1. This causes a mean difference of-14% in 14CO2 concentrations in our simulations at our observational site in Egbert, Canada. On an annual time basis, this additional 14CO2 masks the equivalent of 27–82% of the total annual FFCO2 offset. A pseudo-data experiment suggests that the interannual variability in the masked fraction may cause spurious trends in the ΔFFCO2 estimates of the order of 30% from 2006–2010. In addition, a comparison of the modeled Δ14C levels with our observational time series from 2008–2010 underlines that incorporating the best available 14CO2 emissions significantly increases the agreement. There were also short periods with significant observed Δ14C offsets, which were found to be linked with maintenance periods conducted on these nuclear reactors.

scholarly journals Analysis of Liquid Zone Control Valve Oscillation Problem in CANDU Reactors

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Elnara Nasimi ◽  
Hossam A. Gabbar
Keyword(s):  
Steady State ◽  
Nuclear Power ◽  
Control Valve ◽  
Liquid Zone ◽  
Candu Reactors ◽  
Zone Control ◽  
Power Adjustment ◽  
Oscillation Problem ◽  
Made In

This paper looks at the existing challenges with steady-state Liquid Zone control at some CANDU (CANada Deuterium Uranium) stations, where—contrary to expectations for equilibrium flow—Liquid Zone Control Valve oscillations have proven to be a chronic, unanticipated challenge. Currently, the exact causes of this behaviour are not fully understood, although it is confirmed that the Control Valve oscillations are not due to automatic power adjustment requests or zone level changes due to process leaks. This phenomenon was analysed based on a case study of one domestic nuclear power station to determine whether it could be attributed to inherent controller properties. Next, a proposal is made in an attempt to improve current performance with minimal changes to the existing system hardware and logic using conventional technologies. Finally, a proposal was made to consider Model Predictive Control-based technology to minimize the undesirable Control Valve oscillations at steady state based on the obtained simulation results and discussion of other available alternatives.

NUCLEAR POWER: Ontario to Mothball Two CANDU Reactors

Science ◽  
2005 ◽  
Vol 309 (5739) ◽  
pp. 1312b-1312b
Author(s):  
P. Webster
Keyword(s):  
Nuclear Power ◽  
Candu Reactors
Sign in / Sign up

Export Citation Format

Share Document