Journal of Nuclear Engineering and Radiation Science最新文献_第7页

9Mv Linac Photo-Neutron Interrogation Of Uranium With Advanced Acoustically Tensioned Metastable Fluid Detectors 用先进声张力亚稳流体探测器对铀进行9Mv直线光中子探测

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-07-11 DOI: 10.1115/1.4062951

N. Boyle, S. Ozerov, C. Harabagiu, R. Taleyarkhan

{"title":"9Mv Linac Photo-Neutron Interrogation Of Uranium With Advanced Acoustically Tensioned Metastable Fluid Detectors","authors":"N. Boyle, S. Ozerov, C. Harabagiu, R. Taleyarkhan","doi":"10.1115/1.4062951","DOIUrl":"https://doi.org/10.1115/1.4062951","url":null,"abstract":"\u0000 Active special nuclear material (SNM) photoneutron interrogation research with Acoustically Tensioned Metastable Fluid Detector (ATMFD) sensor technology is discussed which provides evidence for enabling real time detection of special nuclear material (SNM) even when deployed under extreme 15,000 R h-1 (9 MeV endpoint) X-ray beams. Experiments to detect 3.2 kg DU are described with use of two designs of the economical E-ATMFD, viz., E-ATMFD.Ver.0 and E-ATMFD.Ver.1, respectively, at standoffs ranging from 0.1 m to 10 m - including with the E-ATMFD directly within the interrogating beam. Under similar conditions and with 100% photon rejection (i.e., 0 cpm with beam on, and w/o SNM), the E-ATMFD.Ver.1 design was shown capable of ~6x (600%) higher gain at ~10x lower drive powers over E-ATMFD.Ver.0 (with beam on and with SNM). The sensitivity gain rises to ~27x (i.e., 2,700%) with the E-ATMFD.Ver.1 operating at 0.99 W and a background count rate of ~1 cpm. The E-ATMFD.Ver.1 demonstrated 100% photon blindness (0 cpm) while operating at ~0.56 W drive power and placed directly within the beam under 15,000 R/h; including the SNM target led to a count rate of up to 50 cpm - revealing the E-ATMFD.Ver.1 as potentially field-capable for detecting U-based SNMs within seconds from photofission neutron signals, even when deployed directly within the interrogating photon beam.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88946558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Abnormality Attention Diagnosis Model Using One-vs-Rest Classifier in a Nuclear Power Plant 基于一对休息分类器的核电厂多异常注意诊断模型

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-07-08 DOI: 10.3390/jne4030033

Seungyon Cho, Jeonghun Choi, J. Shin, Seung Jun Lee

{"title":"Multi-Abnormality Attention Diagnosis Model Using One-vs-Rest Classifier in a Nuclear Power Plant","authors":"Seungyon Cho, Jeonghun Choi, J. Shin, Seung Jun Lee","doi":"10.3390/jne4030033","DOIUrl":"https://doi.org/10.3390/jne4030033","url":null,"abstract":"Multi-abnormal events, referring to the simultaneous occurrence of multiple single abnormal events in a nuclear power plant, have not been subject to consideration because multi-abnormal events are extremely unlikely to occur and indeed have not yet occurred. Such events, though, would be more challenging to diagnose than general single abnormal events, exacerbating the human error issue. This study introduces an efficient abnormality diagnosis model that covers multi-abnormality diagnosis using a one-vs-rest classifier and compares it with other artificial intelligence models. The multi-abnormality attention diagnosis model deals with multi-label classification problems, for which two methods are proposed. First, a method to effectively cluster single and multi-abnormal events is introduced based on the predicted probability distribution of each abnormal event. Second, a one-vs-rest classifier with high accuracy is employed as an efficient way to obtain knowledge on which particular multi-abnormal events are the most difficult to diagnose and therefore require the most attention to improve the multi-label classification performance in terms of data usage. The developed multi-abnormality attention diagnosis model can reduce human errors of operators due to excessive information and limited time when unexpected multi-abnormal events occur by providing diagnosis results as part of an operator support system.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90196767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementation Of Solar Salt Properties Into Ariant And Simulation Of Pressurized Loss Of Forced Circulation In A High Temperature Gas-Cooled Small Modular Reactor 太阳盐特性在变型中的实现及高温气冷小型模块堆强制循环压力损失的模拟

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-07-07 DOI: 10.1115/1.4062917

Jason Wu, T. Beuthe, Aleksandar Vasić

引用次数: 0

SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models 基于不同半监督机器学习模型的SNM辐射特征分类

IF 0.4

Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-07-04 DOI: 10.3390/jne4030032

Jordan R. Stomps, Paul P. H. Wilson, K. Dayman, Michael J. Willis, James M. Ghawaly, Daniel E. Archer

{"title":"SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models","authors":"Jordan R. Stomps, Paul P. H. Wilson, K. Dayman, Michael J. Willis, James M. Ghawaly, Daniel E. Archer","doi":"10.3390/jne4030032","DOIUrl":"https://doi.org/10.3390/jne4030032","url":null,"abstract":"The timely detection of special nuclear material (SNM) transfers between nuclear facilities is an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled by successful detection and characterization of radiological material movements could greatly enhance the nuclear nonproliferation mission in a range of applications. Supervised machine learning can be used to signal detections when material is present if a model is trained on sufficient volumes of labeled measurements. However, the nuclear monitoring data needed to train robust machine learning models can be costly to label since radiation spectra may require strict scrutiny for characterization. Therefore, this work investigates the application of semi-supervised learning to utilize both labeled and unlabeled data. As a demonstration experiment, radiation measurements from sodium iodide (NaI) detectors are provided by the Multi-Informatics for Nuclear Operating Scenarios (MINOS) venture at Oak Ridge National Laboratory (ORNL) as sample data. Anomalous measurements are identified using a method of statistical hypothesis testing. After background estimation, an energy-dependent spectroscopic analysis is used to characterize an anomaly based on its radiation signatures. In the absence of ground-truth information, a labeling heuristic provides data necessary for training and testing machine learning models. Supervised logistic regression serves as a baseline to compare three semi-supervised machine learning models: co-training, label propagation, and a convolutional neural network (CNN). In each case, the semi-supervised models outperform logistic regression, suggesting that unlabeled data can be valuable when training and demonstrating value in semi-supervised nonproliferation implementations.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84410960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Simple Analytical Model to Predict the Freeze Plug Opening Time in Molten Salt Reactors 预测熔盐堆冻结塞开启时间的简单解析模型

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-06-30 DOI: 10.1115/1.4062879

M. Ilham, T. Okawa

引用次数: 0

An Estimation Method For Bias Error Of Measurements By Utilizing Process Data, An Incidence Matrix And A Reference Instrument For Data Validation And Reconciliation 一种利用过程数据、关联矩阵和参考仪器对测量偏差误差进行估计的方法

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-06-29 DOI: 10.1115/1.4062865

A. Tamura, Yuki Hidaka, Haruhiko Ikeda, Norikazu Hamaura

{"title":"An Estimation Method For Bias Error Of Measurements By Utilizing Process Data, An Incidence Matrix And A Reference Instrument For Data Validation And Reconciliation","authors":"A. Tamura, Yuki Hidaka, Haruhiko Ikeda, Norikazu Hamaura","doi":"10.1115/1.4062865","DOIUrl":"https://doi.org/10.1115/1.4062865","url":null,"abstract":"\u0000 With further applications of AI, IoT, and digital twin technology to plant operation and maintenance, it is becoming increasingly important to ensure data reliability. Data validation and reconciliation (DVR) represents one promising technique to ensure data reliability by minimizing the uncertainty of measurements based on statistics. DVR has been widely applied to nuclear power electrical generation plants in Europe and the United States in recent years. The most important input for DVR analysis is measurement uncertainty. In Japan, performance management of nuclear power plants is often done by measuring condensate flow rate. While the uncertainty of other flowmeters is handled by the JIS standard, the condensate flowmeter is specially calibrated every few cycles. This leads to reduction of effectiveness of DVR analysis due to variations in measurement uncertainty management. To overcome this issue, we propose an estimation method for measurement uncertainty by utilizing process data, an incidence matrix between sensors, and a reference instrument. The conventional method proposed in the previous study only treats the random error. The proposed method quantitatively estimates not only random error but also bias error by considering the uncertainty of the reference instrument. Using several benchmark problems, we found that the proposed method was applicable to various flow conditions, including physically fluctuating flow such as that observed in the feedwater flow in nuclear power plants. We anticipate that the proposed method will promote use of DVR analysis in nuclear power plants in Japan.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90490442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dose Rate Assessment Around the PCFV Release Line During Severe Accident Conditions in Nuclear Power Plant Krsko 核电站严重事故条件下PCFV释放线周围的剂量率评估

IF 0.4

Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-06-20 DOI: 10.1115/1.4062797

D. Grgić, Paulina Duckic, Vesna Benčik, Siniša Šadek

{"title":"Dose Rate Assessment Around the PCFV Release Line During Severe Accident Conditions in Nuclear Power Plant Krsko","authors":"D. Grgić, Paulina Duckic, Vesna Benčik, Siniša Šadek","doi":"10.1115/1.4062797","DOIUrl":"https://doi.org/10.1115/1.4062797","url":null,"abstract":"\u0000 Passive Containment Filtered Vent (PCFV) was installed in Nuclear Power Plant (NPP) Krsko in 2013 as part of the safety upgrade program. It is intended for severe accident consequences prevention and mitigation by ensuring the containment integrity. In this paper, dose rates around the exhaust line of the PCFV system resulting from radioactivity release in case of a severe accident were determined in a four step methodology. The assumed severe accident scenario is a beyond design basis station blackout in NPP Krsko, which was simulated using the MELCOR code. Its results were input for the RADTRAD radiological calculations to obtain the activities released in the containment. These activities were then transformed into the gamma source intensity and spectrum using the ORIGEN-S libraries. This form of the source term is required for Monte Carlo calculations which were performed using the MCNP6.2. Two Monte Carlo calculations were performed. One for which the radiation source was modeled to emanate from the containment atmosphere and the other from the PCFV duct fluid. The main reason for the calculation was to assess limiting dose rates around PCFV duct (radiation monitor location) during actuation after severe accident. That is why the model is simple and conservative. The other task was to demonstrate that this location is not suitable for longer personnel presence in case of equipment failure during the PCFV actuation. Due to conservative assumptions, predicted dose rates are the highest expected at that location for any severe accident scenario.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74224902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interactions Between Molten Sodium and Standard Pipe Insulation 熔融钠与标准管道保温的相互作用

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-06-20 DOI: 10.1115/1.4062798

D. LaBrier, Jordan Harley, Morgan Robbins

{"title":"Interactions Between Molten Sodium and Standard Pipe Insulation","authors":"D. LaBrier, Jordan Harley, Morgan Robbins","doi":"10.1115/1.4062798","DOIUrl":"https://doi.org/10.1115/1.4062798","url":null,"abstract":"\u0000 Safety system design and implementation is critical to the operation of any nuclear plant. For sodium cooled nuclear reactors, hazards external to the reactor core are present in the form of molten sodium that leaks through degraded piping structures. These structures are often clad in high-temperature insulation to preserve the heat needed to keep the sodium molten in the piping. While large sodium leaks are quite noticeable and often result in hazardous fire situations, small leaks of molten sodium are often masked by the shroud of insulation until a large pool of material has collected outside of the failed pipe. This study concentrated on the physical and chemical interactions between molten sodium and standard fiberglass insulation in temperatures ranging from 100 ? to 500 ?. The degradation of the insulation material begins with the volatilization of the organic binder around 250 ?, thereafter the insulation deteriorates at an advanced rate in areas that are in direct contact with the sodium. Chemical profile data was collected for a variety of samples locations that were in contact with the molten sodium, with only a slight increase in the amount of sodium present that can be attributed to the external sodium source. In this way, the molten sodium does not chemically degrade the insulation, but rather accelerates the thermal degradation of the insulation on a local scale, acting as a concentrated heat source to the insulation.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75057733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of Nb On Sintering Process of Gamma Phase Uranium Alloys Fuel Pellets 铌对γ相铀合金燃料球团烧结过程的影响

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-06-20 DOI: 10.1115/1.4062795

Keke Hou, Chao Yan, P. Wang, Changqing Cao, Jun Lin, Yanguang Cui, Junqiang Lu, Libing Zhu

{"title":"Effect of Nb On Sintering Process of Gamma Phase Uranium Alloys Fuel Pellets","authors":"Keke Hou, Chao Yan, P. Wang, Changqing Cao, Jun Lin, Yanguang Cui, Junqiang Lu, Libing Zhu","doi":"10.1115/1.4062795","DOIUrl":"https://doi.org/10.1115/1.4062795","url":null,"abstract":"\u0000 As a candidate material for metallic fuel, U-Mo metal fuel pellets are the most promising. U-Mo and U-Mo-Nb alloy pellets with a certain porosity were successfully prepared by the process of hydrogenation/dehydrogenation - compression molding - argon liquid-phase sintering. In order to study the effect of Nb addition on γ phase uranium alloy fuel pellets, microstructure and thermo-properties of the samples were observed by XRD/SEM etc. Results showed that with the increase of Nb content in the pellets from the non-add to micro-adding, Nb can facilitate the diffusion of Mo into the U matrix, resulting in the formation of a metastable γ-U phase. Meanwhile, during the same liquid phase sintering process of U-Mo fuel pellets, with the increase of Nb content, the number of secondary phases in U-Mo fuel pellets gradually decreased, while the size and number of voids of the secondary phases decreased. And the distribution of voids is more uniform. The specific heat capacity and thermal diffusivity of porous γ phase uranium alloys fuel pellets with different density were measured and thermal conductivity from 373K to 873K were calculated according to the experiment results. It is suggested that the thermal conductivity will increase with the density of pellets.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90023383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Uncertainty and Sensitivity Evaluation of the QUENCH-02 Experiment Simulation Using the ASYST Code 基于ASYST代码的淬火-02试验模拟的不确定度和灵敏度评价

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Journal of Nuclear Engineering and Radiation Science Pub Date : 2023-06-20 DOI: 10.1115/1.4062799

Siniša Šadek, Renato Pavlinac, Karlo Ivanjko, D. Grgić

{"title":"Uncertainty and Sensitivity Evaluation of the QUENCH-02 Experiment Simulation Using the ASYST Code","authors":"Siniša Šadek, Renato Pavlinac, Karlo Ivanjko, D. Grgić","doi":"10.1115/1.4062799","DOIUrl":"https://doi.org/10.1115/1.4062799","url":null,"abstract":"\u0000 Uncertainty and sensitivity methods are increasingly used in safety analyzes of nuclear power plants to address the unreliability of input data, numerical models and, in general, the lack of knowledge regarding certain physical phenomena, in determining safety margins and acceptance criteria. The ASYST code, developed as part of an international nuclear technology ASYST Development and Training Program (ADTP) managed by Innovative Systems Software (ISS), is used to perform an uncertainty analysis of the QUENCH-02 experiment conducted at the Karlsruhe Institute of Technology. The code uses a probabilistic methodology based on the propagation of input uncertainties. The QUENCH facility contains electrically heated PWR fuel rod simulators and the aim of the experiment is to examine hydrogen source term and the behavior of the fuel rod cladding during core reflood.\u0000 For selected input parameters, such as steam/water flow, electrical power and other relevant boundary conditions, it is necessary to define their probability density functions. Input databases are then prepared for individual calculations based on the selected confidence level and confidence interval. The number of performed calculations is 60, large enough to ensure at least 95% coverage of expected output results and uncertainty limits. The results of the calculations are compared with the experimental measurements. The Pearson correlation coefficient is used to obtain correlation between the input uncertain parameters and the output data. Sensitivity analyses cover the influence of variations in the heater electrical power and the steam flow rate on the hydrogen production and the maximum cladding temperature.","PeriodicalId":16756,"journal":{"name":"Journal of Nuclear Engineering and Radiation Science","volume":null,"pages":null},"PeriodicalIF":0.4,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87323080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0