Monitoring the stability of BWR oscillation by nonlinear time series modeling
Monitoring the dynamics evolution of BWR oscillation has great importance in evaluating safety of the nuclear systems. Time series analysis methodology has been widely accepted as a powerful tool for this subject. BWR stability has been so far evaluated by decaying ratio (DR) calculated from the imp...
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| Veröffentlicht in: | Annals of nuclear energy 2001-07, Vol.28 (10), p.953-966 |
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| container_title | Annals of nuclear energy |
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| creator | Shi, Zhaoyun Tamura, Yoshiyasu Ozaki, Tohru |
| description | Monitoring the dynamics evolution of BWR oscillation has great importance in evaluating safety of the nuclear systems. Time series analysis methodology has been widely accepted as a powerful tool for this subject. BWR stability has been so far evaluated by decaying ratio (DR) calculated from the impulse response function of autoregressive (AR) model. To explore much more reliable method for detecting BWR instability, this paper introduces a nonlinear time series analysis approach namely exponential autoregressive (ExpAR) modeling. The ExpAR model is available for revealing types of nonlinear dynamics such as fixed point, limit cycle, and even chaos. Furthermore, the model is real-time estimated so that it is suitable for the purpose of on-line BWR instability detection. Empirical analysis of typical benchmark neutronic signal shows the effectiveness of this proposal. |
| doi_str_mv | 10.1016/S0306-4549(00)00099-2 |
| format | Article |
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Time series analysis methodology has been widely accepted as a powerful tool for this subject. BWR stability has been so far evaluated by decaying ratio (DR) calculated from the impulse response function of autoregressive (AR) model. To explore much more reliable method for detecting BWR instability, this paper introduces a nonlinear time series analysis approach namely exponential autoregressive (ExpAR) modeling. The ExpAR model is available for revealing types of nonlinear dynamics such as fixed point, limit cycle, and even chaos. Furthermore, the model is real-time estimated so that it is suitable for the purpose of on-line BWR instability detection. 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Time series analysis methodology has been widely accepted as a powerful tool for this subject. BWR stability has been so far evaluated by decaying ratio (DR) calculated from the impulse response function of autoregressive (AR) model. To explore much more reliable method for detecting BWR instability, this paper introduces a nonlinear time series analysis approach namely exponential autoregressive (ExpAR) modeling. The ExpAR model is available for revealing types of nonlinear dynamics such as fixed point, limit cycle, and even chaos. Furthermore, the model is real-time estimated so that it is suitable for the purpose of on-line BWR instability detection. Empirical analysis of typical benchmark neutronic signal shows the effectiveness of this proposal.</description><subject>Accident prevention</subject><subject>benchmarks</subject><subject>boiling water reactors</subject><subject>Chaos theory</subject><subject>Functions</subject><subject>Mathematical models</subject><subject>Oscillations</subject><subject>Regression analysis</subject><subject>reliability</subject><subject>safety systems</subject><subject>stability</subject><subject>Time series analysis</subject><issn>0306-4549</issn><issn>1873-2100</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><recordid>eNqFkMtKxDAUhoMoOI4-gpCVl0X1pE2bdCU6eAMHwQsuQ5qmY6RNxiQjzNubmRGXujpw-P5z-RA6JHBGgFTnz1BAldGS1icApwBQ11m-hUaEsyLLCcA2Gv0iu2gvhA8AknNKR2g6ddZE542d4fiucYiyMb2JS-w6fPX2hF1Qpu9lNM7iZomts72xWnoczZBw7Y0OeHCtTu3ZPtrpZB_0wU8do9eb65fJXfbweHs_uXzIVMEgZnmt2pYWZccVb3NS1VRKygsluWxy2uZF09Z1SaTUinesq2gBrCllx4DLlCTFGB1v5s69-1zoEMVggtLpTqvdIghGK1IxxvJEHv1JEsbrqiyrBJYbUHkXgtedmHszSL8UBMRKs1hrFiuHAkCsNYvVgotNTqd_v4z2IgnTVunWeK2iaJ35Z8I3rlKFIQ</recordid><startdate>20010701</startdate><enddate>20010701</enddate><creator>Shi, Zhaoyun</creator><creator>Tamura, Yoshiyasu</creator><creator>Ozaki, Tohru</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7T2</scope><scope>7U2</scope><scope>C1K</scope><scope>7TC</scope></search><sort><creationdate>20010701</creationdate><title>Monitoring the stability of BWR oscillation by nonlinear time series modeling</title><author>Shi, Zhaoyun ; Tamura, Yoshiyasu ; Ozaki, Tohru</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-29cdd435f8c8d21694aa483ca8ab24d23bd9951aaec8f7f64307b5af708acdd13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Accident prevention</topic><topic>benchmarks</topic><topic>boiling water reactors</topic><topic>Chaos theory</topic><topic>Functions</topic><topic>Mathematical models</topic><topic>Oscillations</topic><topic>Regression analysis</topic><topic>reliability</topic><topic>safety systems</topic><topic>stability</topic><topic>Time series analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shi, Zhaoyun</creatorcontrib><creatorcontrib>Tamura, Yoshiyasu</creatorcontrib><creatorcontrib>Ozaki, Tohru</creatorcontrib><collection>CrossRef</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Safety Science and Risk</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Mechanical Engineering Abstracts</collection><jtitle>Annals of nuclear energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shi, Zhaoyun</au><au>Tamura, Yoshiyasu</au><au>Ozaki, Tohru</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Monitoring the stability of BWR oscillation by nonlinear time series modeling</atitle><jtitle>Annals of nuclear energy</jtitle><date>2001-07-01</date><risdate>2001</risdate><volume>28</volume><issue>10</issue><spage>953</spage><epage>966</epage><pages>953-966</pages><issn>0306-4549</issn><eissn>1873-2100</eissn><abstract>Monitoring the dynamics evolution of BWR oscillation has great importance in evaluating safety of the nuclear systems. Time series analysis methodology has been widely accepted as a powerful tool for this subject. BWR stability has been so far evaluated by decaying ratio (DR) calculated from the impulse response function of autoregressive (AR) model. To explore much more reliable method for detecting BWR instability, this paper introduces a nonlinear time series analysis approach namely exponential autoregressive (ExpAR) modeling. The ExpAR model is available for revealing types of nonlinear dynamics such as fixed point, limit cycle, and even chaos. Furthermore, the model is real-time estimated so that it is suitable for the purpose of on-line BWR instability detection. Empirical analysis of typical benchmark neutronic signal shows the effectiveness of this proposal.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/S0306-4549(00)00099-2</doi><tpages>14</tpages></addata></record> |
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| language | eng |
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| source | Elsevier ScienceDirect Journals Complete |
| subjects | Accident prevention benchmarks boiling water reactors Chaos theory Functions Mathematical models Oscillations Regression analysis reliability safety systems stability Time series analysis |
| title | Monitoring the stability of BWR oscillation by nonlinear time series modeling |
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