The identification of chaos in the two-phase natural circulation system under rolling motion can provide theoretical guidance for forecasting and control of natural circulation flow instability. The surrogate-data technique is one of effective methods to identify the chaos in the time series exactly. It can avoid the limitation of the positively identifying chaos. In this paper, correlation dimension and principal component analysis (PCA) was used as the identification evidence; the surrogate-data technique was used for the identification of chaos in time series of the irregular complex flow oscillations. The results indicate that there is chaos in the natural circulation system under rolling motion and the surrogate-data technique can identify chaos exactly.

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