Assessment of linear and non-linear auto-regressive methods for BWR stability monitoring

A. Manera, Robert Zboray, T. H.J.J. Van Der Hagen

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    A benchmark has been performed to compare the performances of exponential autoregressive (ExpAR) models against linear autoregressive (AR) models with respect to boiling water reactor stability monitoring. The well-known March-Leuba reduced-order model is used to generate the time-series to be analysed, since this model is able to reproduce the most significant non-linear behaviour of boiling water reactors (i.e. converging, diverging and limit-cycle oscillations). In this way the stability characteristics of the signals to be analysed are known a priori. An application to experimental time-traces measured on a thermalhydraulic natural circulation loop is reported as well. All methods perform equally well in determining the stability characteristics of the analysed signals.

    Original languageEnglish (US)
    Pages (from-to)321-327
    Number of pages7
    JournalProgress in Nuclear Energy
    Volume43
    Issue number1-4 SPEC
    DOIs
    StatePublished - Jan 1 2003

    Fingerprint

    Boiling water reactors
    Monitoring
    monitoring
    Time series
    oscillation
    time series
    water
    method
    reactor

    All Science Journal Classification (ASJC) codes

    • Nuclear Energy and Engineering
    • Safety, Risk, Reliability and Quality
    • Energy Engineering and Power Technology
    • Waste Management and Disposal

    Cite this

    Manera, A. ; Zboray, Robert ; Van Der Hagen, T. H.J.J. / Assessment of linear and non-linear auto-regressive methods for BWR stability monitoring. In: Progress in Nuclear Energy. 2003 ; Vol. 43, No. 1-4 SPEC. pp. 321-327.
    @article{cc8b240206b143eeab550a46861885d6,
    title = "Assessment of linear and non-linear auto-regressive methods for BWR stability monitoring",
    abstract = "A benchmark has been performed to compare the performances of exponential autoregressive (ExpAR) models against linear autoregressive (AR) models with respect to boiling water reactor stability monitoring. The well-known March-Leuba reduced-order model is used to generate the time-series to be analysed, since this model is able to reproduce the most significant non-linear behaviour of boiling water reactors (i.e. converging, diverging and limit-cycle oscillations). In this way the stability characteristics of the signals to be analysed are known a priori. An application to experimental time-traces measured on a thermalhydraulic natural circulation loop is reported as well. All methods perform equally well in determining the stability characteristics of the analysed signals.",
    author = "A. Manera and Robert Zboray and {Van Der Hagen}, {T. H.J.J.}",
    year = "2003",
    month = "1",
    day = "1",
    doi = "10.1016/S0149-1970(03)00005-2",
    language = "English (US)",
    volume = "43",
    pages = "321--327",
    journal = "Progress in Nuclear Energy",
    issn = "0149-1970",
    publisher = "Elsevier Limited",
    number = "1-4 SPEC",

    }

    Assessment of linear and non-linear auto-regressive methods for BWR stability monitoring. / Manera, A.; Zboray, Robert; Van Der Hagen, T. H.J.J.

    In: Progress in Nuclear Energy, Vol. 43, No. 1-4 SPEC, 01.01.2003, p. 321-327.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Assessment of linear and non-linear auto-regressive methods for BWR stability monitoring

    AU - Manera, A.

    AU - Zboray, Robert

    AU - Van Der Hagen, T. H.J.J.

    PY - 2003/1/1

    Y1 - 2003/1/1

    N2 - A benchmark has been performed to compare the performances of exponential autoregressive (ExpAR) models against linear autoregressive (AR) models with respect to boiling water reactor stability monitoring. The well-known March-Leuba reduced-order model is used to generate the time-series to be analysed, since this model is able to reproduce the most significant non-linear behaviour of boiling water reactors (i.e. converging, diverging and limit-cycle oscillations). In this way the stability characteristics of the signals to be analysed are known a priori. An application to experimental time-traces measured on a thermalhydraulic natural circulation loop is reported as well. All methods perform equally well in determining the stability characteristics of the analysed signals.

    AB - A benchmark has been performed to compare the performances of exponential autoregressive (ExpAR) models against linear autoregressive (AR) models with respect to boiling water reactor stability monitoring. The well-known March-Leuba reduced-order model is used to generate the time-series to be analysed, since this model is able to reproduce the most significant non-linear behaviour of boiling water reactors (i.e. converging, diverging and limit-cycle oscillations). In this way the stability characteristics of the signals to be analysed are known a priori. An application to experimental time-traces measured on a thermalhydraulic natural circulation loop is reported as well. All methods perform equally well in determining the stability characteristics of the analysed signals.

    UR - http://www.scopus.com/inward/record.url?scp=0038078189&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=0038078189&partnerID=8YFLogxK

    U2 - 10.1016/S0149-1970(03)00005-2

    DO - 10.1016/S0149-1970(03)00005-2

    M3 - Article

    AN - SCOPUS:0038078189

    VL - 43

    SP - 321

    EP - 327

    JO - Progress in Nuclear Energy

    JF - Progress in Nuclear Energy

    SN - 0149-1970

    IS - 1-4 SPEC

    ER -