原子炉炉心冷却系での流動異常の診断に対するARモデルの適用性

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  • Applicability of the AR Model to the Diagnosis of Flow Anomaly in Reactor Cooling Channels
  • ゲンシロ ロシン レイキャクケイ デ ノ リュウドウ イジョウ ノ シンダン

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In this paper, we examine the applicability of the multivariable autoregressive data fitting (AR model) to the detection of flow anomaly in reactor cooling channels.<br>Experiments were carried out with an out-of-pile loop, through which Ar-water two-phase flow circulated in a steady state condition. Fluctuation signals observed by two pressure transducers as well as two pairs of void taps were sampled and analized, by using on-line computers. A computer code for data processing was developed under the guidance of the familiar AR model algorithm proposed by Akaike et al.. Still, the method of maximum likelihood estimation was adopted to determine the order of the AR model.<br>Power spectral densities produced by the AR model were contrasted with those calculated by the conventional method developed by Blackman-Tukey, that is a fast Fourier transform algorithm, to yeild good consistency between them. The AR model presents other useful information including one index named “Impulse Response Function” and anthor “Relative Power Contribution Rate”. The former index allows us to explain resonably the experimental results of pressure propagation characteristics. Using the latter index, on the other hand, we can get the spectra of noise source coherent to each variable. When those source spectra are assumed to be equal to the input disturbances of a linear theoretical model of the local flow boiling, the theoretically estimated power spectral densities are in fairly good agreement with the observed ones.<br>Following these studies, we can expect the applicability of the AR model to the detection and analysis of a flow anomaly, when the model is used with the practical idea of system identification proposed here.

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