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

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

    Research output: Contribution to journalArticlepeer-review

    5 Scopus citations


    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
    Issue number1-4 SPEC
    StatePublished - 2003

    All Science Journal Classification (ASJC) codes

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


    Dive into the research topics of 'Assessment of linear and non-linear auto-regressive methods for BWR stability monitoring'. Together they form a unique fingerprint.

    Cite this