Smart support system for diagnosing severe accidents in nuclear power plants
Recently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2018-05-01
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| Series: | Nuclear Engineering and Technology |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573318301104 |
| _version_ | 1818620700184805376 |
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| author | Kwae Hwan Yoo Ju Hyun Back Man Gyun Na Seop Hur Hyeonmin Kim |
| author_facet | Kwae Hwan Yoo Ju Hyun Back Man Gyun Na Seop Hur Hyeonmin Kim |
| author_sort | Kwae Hwan Yoo |
| collection | DOAJ |
| description | Recently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this study, a smart support system was developed by integrating accident prediction functions from previous research and enhancing their prediction capability. Through this system, operators can predict accident scenarios, accident locations, and accident information in advance. In addition, it is possible to decide on the integrity of instruments and predict the life of instruments. The data were obtained using Modular Accident Analysis Program code to simulate severe accident scenarios for the Optimized Power Reactor 1000. The prediction of the accident scenario, accident location, and accident information was conducted using artificial intelligence methods. Keywords: Artificial Intelligence, Diagnosis, Operator Support, Severe Accident, Smart Support System |
| first_indexed | 2024-12-16T17:57:33Z |
| format | Article |
| id | doaj.art-c1403fbb185646b3b0ee9206ca2087c3 |
| institution | Directory Open Access Journal |
| issn | 1738-5733 |
| language | English |
| last_indexed | 2024-12-16T17:57:33Z |
| publishDate | 2018-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Nuclear Engineering and Technology |
| spelling | doaj.art-c1403fbb185646b3b0ee9206ca2087c32022-12-21T22:22:08ZengElsevierNuclear Engineering and Technology1738-57332018-05-01504562569Smart support system for diagnosing severe accidents in nuclear power plantsKwae Hwan Yoo0Ju Hyun Back1Man Gyun Na2Seop Hur3Hyeonmin Kim4Department of Nuclear Engineering, CHOSUN University, 309 Pilmun-daero, Dong-gu, Gwangju, 501-759, Republic of KoreaDepartment of Nuclear Engineering, CHOSUN University, 309 Pilmun-daero, Dong-gu, Gwangju, 501-759, Republic of KoreaDepartment of Nuclear Engineering, CHOSUN University, 309 Pilmun-daero, Dong-gu, Gwangju, 501-759, Republic of Korea; Corresponding author.Korea Atomic Energy Research Institute, 111 Daedeok-daero, 989 Beon-gil, Yuseoung-gu, Daejeon, Republic of KoreaKorea Atomic Energy Research Institute, 111 Daedeok-daero, 989 Beon-gil, Yuseoung-gu, Daejeon, Republic of KoreaRecently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this study, a smart support system was developed by integrating accident prediction functions from previous research and enhancing their prediction capability. Through this system, operators can predict accident scenarios, accident locations, and accident information in advance. In addition, it is possible to decide on the integrity of instruments and predict the life of instruments. The data were obtained using Modular Accident Analysis Program code to simulate severe accident scenarios for the Optimized Power Reactor 1000. The prediction of the accident scenario, accident location, and accident information was conducted using artificial intelligence methods. Keywords: Artificial Intelligence, Diagnosis, Operator Support, Severe Accident, Smart Support Systemhttp://www.sciencedirect.com/science/article/pii/S1738573318301104 |
| spellingShingle | Kwae Hwan Yoo Ju Hyun Back Man Gyun Na Seop Hur Hyeonmin Kim Smart support system for diagnosing severe accidents in nuclear power plants Nuclear Engineering and Technology |
| title | Smart support system for diagnosing severe accidents in nuclear power plants |
| title_full | Smart support system for diagnosing severe accidents in nuclear power plants |
| title_fullStr | Smart support system for diagnosing severe accidents in nuclear power plants |
| title_full_unstemmed | Smart support system for diagnosing severe accidents in nuclear power plants |
| title_short | Smart support system for diagnosing severe accidents in nuclear power plants |
| title_sort | smart support system for diagnosing severe accidents in nuclear power plants |
| url | http://www.sciencedirect.com/science/article/pii/S1738573318301104 |
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