• 제목/요약/키워드: Nuclear components

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A review of missing video frame estimation techniques for their suitability analysis in NPP

  • Chaubey, Mrityunjay;Singh, Lalit Kumar;Gupta, Manjari
    • Nuclear Engineering and Technology
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    • 제54권4호
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    • pp.1153-1160
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    • 2022
  • The application of video processing techniques are useful for the safety of nuclear power plants by tracking the people online on video to estimate the dose received by staff during work in nuclear plants. Nuclear reactors remotely visually controlled to evaluate the plant's condition using video processing techniques. Internal reactor components should be frequently inspected but in current scenario however involves human technicians, who review inspection videos and identify the costly, time-consuming and subjective cracks on metallic surfaces of underwater components. In case, if any frame of the inspection video degraded/corrupted/missed due to noise or any other factor, then it may cause serious safety issue. The problem of missing/degraded/corrupted video frame estimation is a challenging problem till date. In this paper a systematic literature review on video processing techniques is carried out, to perform their suitability analysis for NPP applications. The limitation of existing approaches are also identified along with a roadmap to overcome these limitations.

RELIABILITY ANALYSIS OF DIGITAL SYSTEMS IN A PROBABILISTIC RISK ANALYSIS FOR NUCLEAR POWER PLANTS

  • Authen, Stefan;Holmberg, Jan-Erik
    • Nuclear Engineering and Technology
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    • 제44권5호
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    • pp.471-482
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    • 2012
  • To assess the risk of nuclear power plant operation and to determine the risk impact of digital systems, there is a need to quantitatively assess the reliability of the digital systems in a justifiable manner. The Probabilistic Risk Analysis (PRA) is a tool which can reveal shortcomings of the NPP design in general and PRA analysts have not had sufficient guiding principles in modelling particular digital components malfunctions. Currently digital I&C systems are mostly analyzed simply and conventionally in PRA, based on failure mode and effects analysis and fault tree modelling. More dynamic approaches are still in the trial stage and can be difficult to apply in full scale PRA-models. As basic events CPU failures, application software failures and common cause failures (CCF) between identical components are modelled.The primary goal is to model dependencies. However, it is not clear which failure modes or system parts CCF:s should be postulated for. A clear distinction can be made between the treatment of protection and control systems. There is a general consensus that protection systems shall be included in PRA, while control systems can be treated in a limited manner. OECD/NEA CSNI Working Group on Risk Assessment (WGRisk) has set up a task group, called DIGREL, to develop taxonomy of failure modes of digital components for the purposes of PRA. The taxonomy is aimed to be the basis of future modelling and quantification efforts. It will also help to define a structure for data collection and to review PRA studies.

Study of contact melting of plate bundles by molten material in severe reactor accidents

  • J.J. Ma;W.Z. Chen;H.G. Xiao
    • Nuclear Engineering and Technology
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    • 제55권11호
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    • pp.4266-4273
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    • 2023
  • In a severe reactor accident, a crust will form on the surface of the molten material during the core melting process. The crust will have a contact melting with the internal components of the reactor. In this paper, the contact melting process of the molten material on the austenitic stainless steel plate bundles is studied. The contact melting model of parabolic molten material on the plate bundles is proposed, and the rule and main effect factors of the contact melting are analyzed. The results show that the melting velocity is proportional to the slope of the paraboloid, the heat flux and the distance between two plates D. The influence of melt gravity and the plate width on melting velocity is negligible. The thickness of the molten liquid film is proportional to the heat flux and plate width, and it is inversely proportional to the gravity. With the increase of D, the liquid film thickness decreases at first and then increases gradually. The liquid film thickness has a minimum against D. When the width of the plate is small, the width of the plate is the main factor affecting the thickness of the liquid film. The parameters are coupled with each other. In a severe reactor accident, the wider internal components of reactor, which can increase the thickness of the melting liquid film and reduce the net input heat flux from the molten material to the components, are the effective measures to delay the melting process.

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

  • Ik Jae Jin;Do Yeong Lim;In Cheol Bang
    • Nuclear Engineering and Technology
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    • 제55권2호
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    • pp.493-505
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    • 2023
  • Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.