• Title/Summary/Keyword: Water Accident

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Simulation of Water Pollution Accident with Water Quality Model (수질모형을 이용한 수질오염사고의 모의분석)

  • Choi, Hyun Gu;Park, Jun Hyung;Han, Kun Yeun
    • Journal of Environmental Impact Assessment
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    • v.23 no.3
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    • pp.177-186
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    • 2014
  • Depending on the change of lifestyle and the improvement of people's living standards and rapid industrialization, urbanization of recent, demand for water is increasing rapidly. So emissions of domestic wastewater and various industrial waste water has increased, and water quality is worsening day by day. Therefore, in order to provide a measure against the occurrence of water pollution accident, this study was tried to simulate water pollution accident. This study simulated 2008 Gimcheon phenol accident using 1,2-D model, and analyze scenario for prevent of water pollution accident. Consequently the developed 1-D model presents high reappearance when compared with 2-D model, and has been able to obtain results in a short simulation run time. This study will contribute to the water pollution incident response prediction system and water quality analysis in the future.

EVALUATION OF AN ACCIDENT MANAGEMENT STRATEGY OF EMERGENCY WATER INJECTION USING FIRE ENGINES IN A TYPICAL PRESSURIZED WATER REACTOR

  • PARK, SOO-YONG;AHN, KWANG-IL
    • Nuclear Engineering and Technology
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    • v.47 no.6
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    • pp.719-728
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    • 2015
  • Following the Fukushima accident, a special safety inspection was conducted in Korea. The inspection results show that Korean nuclear power plants have no imminent risk for expected maximum potential earthquake or coastal flooding. However long- and short-term safety improvements do need to be implemented. One of the measures to increase the mitigation capability during a prolonged station blackout (SBO) accident is installing injection flow paths to provide emergency cooling water of external sources using fire engines to the steam generators or reactor cooling systems. This paper illustrates an evaluation of the effectiveness of external cooling water injection strategies using fire trucks during a potential extended SBO accident in a 1,000 MWe pressurized water reactor. With regard to the effectiveness of external cooling water injection strategies using fire engines, the strategies are judged to be very feasible for a long-term SBO, but are not likely to be effective for a short-term SBO.

Evaluating direct vessel injection accident-event progression of AP1000 and key figures of merit to support the design and development of water-cooled small modular reactors

  • Hossam H. Abdellatif;Palash K. Bhowmik;David Arcilesi;Piyush Sabharwall
    • Nuclear Engineering and Technology
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    • v.56 no.6
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    • pp.2375-2387
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    • 2024
  • The passive safety systems (PSSs) within water-cooled reactors are meticulously engineered to function autonomously, requiring no external power source or manual intervention. They depend exclusively on inherent natural forces and the fundamental principles of reactor physics, such as gravity, natural convection, and phase changes, to manage, alleviate, and avert the release of radioactive materials into the environment during accident scenarios like a loss-of-coolant accident (LOCA). PSSs are already integrated into such operating commercial reactors as the Advanced Pressurized Reactor-1000 MWe (AP1000) and the Water-Water Energetic Reactor-1200 MWe (WWER-1200) are adopted in most of the upcoming small modular reactor (SMR) designs. Examples of water-cooled SMR PSSs are the passive emergency core-cooling system (ECCS), passive containment cooling system (PCCS), and passive decay-heat removal system, the designs of which vary based on reactor system-design requirements. However, understanding the accident-event progression and phases of a LOCA is pivotal for adopting a specific PSS for a new SMR design. This study covers the accident-event progression for direct vessel injection (DVI) small-break loss-of-coolant accident (SB-LOCA), associated physics phenomena, knowledge gaps, and important figures of merit (FOMs) that may need to be evaluated and assessed to validate thermal-hydraulics models with an available experimental dataset to support new SMR design and development.

COMPARATIVE ANALYSIS OF STATION BLACKOUT ACCIDENT PROGRESSION IN TYPICAL PWR, BWR, AND PHWR

  • Park, Soo-Yong;Ahn, Kwang-Il
    • Nuclear Engineering and Technology
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    • v.44 no.3
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    • pp.311-322
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    • 2012
  • Since the crisis at the Fukushima plants, severe accident progression during a station blackout accident in nuclear power plants is recognized as a very important area for accident management and emergency planning. The purpose of this study is to investigate the comparative characteristics of anticipated severe accident progression among the three typical types of nuclear reactors. A station blackout scenario, where all off-site power is lost and the diesel generators fail, is simulated as an initiating event of a severe accident sequence. In this study a comparative analysis was performed for typical pressurized water reactor (PWR), boiling water reactor (BWR), and pressurized heavy water reactor (PHWR). The study includes the summarization of design differences that would impact severe accident progressions, thermal hydraulic/severe accident phenomenological analysis during a station blackout initiated-severe accident; and an investigation of the core damage process, both within the reactor vessel before it fails and in the containment afterwards, and the resultant impact on the containment.

Analysis of articles on water quality accidents in the water distribution networks using big data topic modelling and sentiment analysis (빅데이터 토픽모델링과 감성분석을 활용한 물공급과정에서의 수질사고 기사 분석)

  • Hong, Sung-Jin;Yoo, Do-Guen
    • Journal of Korea Water Resources Association
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    • v.55 no.spc1
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    • pp.1235-1249
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    • 2022
  • This study applied the web crawling technique for extracting big data news on water quality accidents in the water supply system and presented the algorithm in a procedural way to obtain accurate water quality accident news. In addition, in the case of a large-scale water quality accident, development patterns such as accident recognition, accident spread, accident response, and accident resolution appear according to the occurrence of an accident. That is, the analysis of the development of water quality accidents through key keywords and sentiment analysis for each stage was carried out in detail based on case studies, and the meanings were analyzed and derived. The proposed methodology was applied to the larval accident period of Incheon Metropolitan City in 2020 and analyzed. As a result, in a situation where the disclosure of information that directly affects consumers, such as water quality accidents, is restricted, the tone of news articles and media reports about water quality accidents with long-term damage in the event of an accident and the degree of consumer pride clearly change over time. could check This suggests the need to prepare consumer-centered policies to increase consumer positivity, although rapid restoration of facilities is very important for the development of water quality accidents from the supplier's point of view.

PREDICTION OF THE REACTOR VESSEL WATER LEVEL USING FUZZY NEURAL NETWORKS IN SEVERE ACCIDENT CIRCUMSTANCES OF NPPS

  • Park, Soon Ho;Kim, Dae Seop;Kim, Jae Hwan;Na, Man Gyun
    • Nuclear Engineering and Technology
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    • v.46 no.3
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    • pp.373-380
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    • 2014
  • Safety-related parameters are very important for confirming the status of a nuclear power plant. In particular, the reactor vessel water level has a direct impact on the safety fortress by confirming reactor core cooling. In this study, the reactor vessel water level under the condition of a severe accident, where the water level could not be measured, was predicted using a fuzzy neural network (FNN). The prediction model was developed using training data, and validated using independent test data. The data was generated from simulations of the optimized power reactor 1000 (OPR1000) using MAAP4 code. The informative data for training the FNN model was selected using the subtractive clustering method. The prediction performance of the reactor vessel water level was quite satisfactory, but a few large errors were occasionally observed. To check the effect of instrument errors, the prediction model was verified using data containing artificially added errors. The developed FNN model was sufficiently accurate to be used to predict the reactor vessel water level in severe accident situations where the integrity of the reactor vessel water level sensor is compromised. Furthermore, if the developed FNN model can be optimized using a variety of data, it should be possible to predict the reactor vessel water level precisely.

A Numerical Study on the Mitigation Effect of Water Curtain for SiCl4 Toxic Gas Release (SiCl4 누출 시 수막설비의 방재효과에 대한 수치 해석 연구)

  • Tae In Ryu;Eunmi Lee;Seungha Kim;Seong-mi Kang;Chang-hyun Shin;Seungbum Jo
    • Journal of the Korean Society of Safety
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    • v.38 no.3
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    • pp.43-50
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    • 2023
  • Silicone tetrachloride (SiCl4) leak accidents cause enormous human and environmental damage because it is highly toxic. Some handling facilities use water curtains to reduce the impact range of SiCl4. Although the water curtain is known as one of the most efficient technologies for post-release mitigation, its effect on reducing SiCl4 concentration needs to be investigated scientifically and quantitatively. In this study, three-dimensional computational fluid dynamics (CFD) was used to investigate the physical and chemical effects of water curtains as a release-mitigation system for SiCl4. SiCl4 is released and dispersed five seconds prior to the operation of the water curtain. Once the water curtain works, the SiCl4 reacts chemically with the water and its concentration decreases rapidly; it reaches an emergency response planning guidelines level 2 (ERPG-2) of 5 parts per million (ppm) at about 570 m. We observed, however, that the physical effect of water curtains on reducing SiCl4 concentration is insignificant when the chemical effect is eliminated. These results are crucial since they can be a scientific and quantitative basis for the 'technical guidelines for estimating the accident affected range'. In order to protect the public from chemical accidents, more toxic gas mitigation technologies need to be developed.

Reactor Vessel Water Level Estimation During Severe Accidents Using Cascaded Fuzzy Neural Networks

  • Kim, Dong Yeong;Yoo, Kwae Hwan;Choi, Geon Pil;Back, Ju Hyun;Na, Man Gyun
    • Nuclear Engineering and Technology
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    • v.48 no.3
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    • pp.702-710
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    • 2016
  • Global concern and interest in the safety of nuclear power plants have increased considerably since the Fukushima accident. In the event of a severe accident, the reactor vessel water level cannot be measured. The reactor vessel water level has a direct impact on confirming the safety of reactor core cooling. However, in the event of a severe accident, it may be possible to estimate the reactor vessel water level by employing other information. The cascaded fuzzy neural network (CFNN) model can be used to estimate the reactor vessel water level through the process of repeatedly adding fuzzy neural networks. The developed CFNN model was found to be sufficiently accurate for estimating the reactor vessel water level when the sensor performance had deteriorated. Therefore, the developed CFNN model can help provide effective information to operators in the event of a severe accident.

Effect of Spray System on Fission Product Distribution in Containment During a Severe Accident in a Two-Loop Pressurized Water Reactor

  • Dehjourian, Mehdi;Rahgoshay, Mohammad;Sayareh, Reza;Jahanfarnia, Gholamreza;Shirani, Amir Saied
    • Nuclear Engineering and Technology
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    • v.48 no.4
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    • pp.975-981
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    • 2016
  • The containment response during the first 24 hours of a low-pressure severe accident scenario in a nuclear power plant with a two-loop Westinghouse-type pressurized water reactor was simulated with the CONTAIN 2.0 computer code. The accident considered in this study is a large-break loss-of-coolant accident, which is not successfully mitigated by the action of safety systems. The analysis includes pressure and temperature responses, as well as investigation into the influence of spray on the retention of fission products and the prevention of hydrogen combustion in the containment.

Nuclear reactor vessel water level prediction during severe accidents using deep neural networks

  • Koo, Young Do;An, Ye Ji;Kim, Chang-Hwoi;Na, Man Gyun
    • Nuclear Engineering and Technology
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    • v.51 no.3
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    • pp.723-730
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    • 2019
  • Acquiring instrumentation signals generated from nuclear power plants (NPPs) is essential to maintain nuclear reactor integrity or to mitigate an abnormal state under normal operating conditions or severe accident circumstances. However, various safety-critical instrumentation signals from NPPs cannot be accurately measured on account of instrument degradation or failure under severe accident circumstances. Reactor vessel (RV) water level, which is an accident monitoring variable directly related to reactor cooling and prevention of core exposure, was predicted by applying a few signals to deep neural networks (DNNs) during severe accidents in NPPs. Signal data were obtained by simulating the postulated loss-of-coolant accidents at hot- and cold-legs, and steam generator tube rupture using modular accident analysis program code as actual NPP accidents rarely happen. To optimize the DNN model for RV water level prediction, a genetic algorithm was used to select the numbers of hidden layers and nodes. The proposed DNN model had a small root mean square error for RV water level prediction, and performed better than the cascaded fuzzy neural network model of the previous study. Consequently, the DNN model is considered to perform well enough to provide supporting information on the RV water level to operators.