Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems
The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentati...
Ausführliche Beschreibung
Autor*in: |
Park, JaeKwan [verfasserIn] Kim, TaekKyu [verfasserIn] Koo, SeoRyong [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Progress in nuclear energy - Amsterdam [u.a.] : Elsevier Science, 1977, 164 |
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Übergeordnetes Werk: |
volume:164 |
DOI / URN: |
10.1016/j.pnucene.2023.104842 |
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Katalog-ID: |
ELV064975843 |
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520 | |a The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. | ||
650 | 4 | |a Verification and validation | |
650 | 4 | |a Artificial intelligence | |
650 | 4 | |a Deep learning model | |
650 | 4 | |a Software development process | |
650 | 4 | |a Software testing | |
700 | 1 | |a Kim, TaekKyu |e verfasserin |4 aut | |
700 | 1 | |a Koo, SeoRyong |e verfasserin |4 aut | |
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10.1016/j.pnucene.2023.104842 doi (DE-627)ELV064975843 (ELSEVIER)S0149-1970(23)00277-9 DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Park, JaeKwan verfasserin (orcid)0000-0002-3024-0174 aut Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. Verification and validation Artificial intelligence Deep learning model Software development process Software testing Kim, TaekKyu verfasserin aut Koo, SeoRyong verfasserin aut Enthalten in Progress in nuclear energy Amsterdam [u.a.] : Elsevier Science, 1977 164 Online-Ressource (DE-627)320412032 (DE-600)2001442-9 (DE-576)251938190 0149-1970 nnns volume:164 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 164 |
spelling |
10.1016/j.pnucene.2023.104842 doi (DE-627)ELV064975843 (ELSEVIER)S0149-1970(23)00277-9 DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Park, JaeKwan verfasserin (orcid)0000-0002-3024-0174 aut Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. Verification and validation Artificial intelligence Deep learning model Software development process Software testing Kim, TaekKyu verfasserin aut Koo, SeoRyong verfasserin aut Enthalten in Progress in nuclear energy Amsterdam [u.a.] : Elsevier Science, 1977 164 Online-Ressource (DE-627)320412032 (DE-600)2001442-9 (DE-576)251938190 0149-1970 nnns volume:164 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 164 |
allfields_unstemmed |
10.1016/j.pnucene.2023.104842 doi (DE-627)ELV064975843 (ELSEVIER)S0149-1970(23)00277-9 DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Park, JaeKwan verfasserin (orcid)0000-0002-3024-0174 aut Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. Verification and validation Artificial intelligence Deep learning model Software development process Software testing Kim, TaekKyu verfasserin aut Koo, SeoRyong verfasserin aut Enthalten in Progress in nuclear energy Amsterdam [u.a.] : Elsevier Science, 1977 164 Online-Ressource (DE-627)320412032 (DE-600)2001442-9 (DE-576)251938190 0149-1970 nnns volume:164 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 164 |
allfieldsGer |
10.1016/j.pnucene.2023.104842 doi (DE-627)ELV064975843 (ELSEVIER)S0149-1970(23)00277-9 DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Park, JaeKwan verfasserin (orcid)0000-0002-3024-0174 aut Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. Verification and validation Artificial intelligence Deep learning model Software development process Software testing Kim, TaekKyu verfasserin aut Koo, SeoRyong verfasserin aut Enthalten in Progress in nuclear energy Amsterdam [u.a.] : Elsevier Science, 1977 164 Online-Ressource (DE-627)320412032 (DE-600)2001442-9 (DE-576)251938190 0149-1970 nnns volume:164 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 164 |
allfieldsSound |
10.1016/j.pnucene.2023.104842 doi (DE-627)ELV064975843 (ELSEVIER)S0149-1970(23)00277-9 DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Park, JaeKwan verfasserin (orcid)0000-0002-3024-0174 aut Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. Verification and validation Artificial intelligence Deep learning model Software development process Software testing Kim, TaekKyu verfasserin aut Koo, SeoRyong verfasserin aut Enthalten in Progress in nuclear energy Amsterdam [u.a.] : Elsevier Science, 1977 164 Online-Ressource (DE-627)320412032 (DE-600)2001442-9 (DE-576)251938190 0149-1970 nnns volume:164 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 164 |
language |
English |
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Enthalten in Progress in nuclear energy 164 volume:164 |
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Enthalten in Progress in nuclear energy 164 volume:164 |
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verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems |
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Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems |
abstract |
The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. |
abstractGer |
The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. |
abstract_unstemmed |
The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. This approach serves as a foundation for fostering understanding and agreement among system engineers, operating licensees, and regulatory bodies on the use of AI components in nuclear power plants. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">ELV064975843</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20231005073341.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">231005s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.pnucene.2023.104842</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV064975843</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0149-1970(23)00277-9</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">52.50</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Park, JaeKwan</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-3024-0174</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Verification strategy for artificial intelligence components in nuclear plant instrumentation and control systems</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The application of artificial intelligence (AI) systems in nuclear power plants has the potential to facilitate significant advancements in the industry. However, nuclear system engineers and regulators have expressed concerns regarding the reliability of AI components owing to a lack of documentation and appropriate verification methods that differ from those used for traditional software. Accordingly, this study proposes a systematic approach for the verification and validation of AI components based on nuclear software regulatory guidelines. The proposed strategy includes process verification and functional testing activities specifically tailored to AI components for instrumentation and control systems. 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