Doctoral Dissertations

Date of Award

12-1990

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Nuclear Engineering

Major Professor

Rafael B. Perez

Committee Members

J. Milton Bailey, Laurence F. Miller, Belle R. Upadhyaya

Abstract

The methodology developed in this dissertation uses theoretical models of the neutron power spectral density (PSD) from an ex-core neutron detector in a pressurized water reactor (PWR) and nuclear plant noise data taken under normal operating conditions to quantify the dynamic state of the plant in terms of physically significant parameters and to provide representations of the noise descriptors that characterize the plant condition for evaluation of diagnostic content. The procedure advanced in this research allows the investigation of both neutronic-thermal-hydraulic feedback effects and mechanical motion effects due to the disparate types of models the methodology can accommodate. This flexibility allowed the techniques presented in this work to be applied to spectral data over an extensive frequency range. Therefore, the behavior of the neutron noise in response to diverse driving sources was evaluated, diagnosed and trended. The systematic approach used in this methodology can provide the basis for automated, on-line diagnostic applications using neutron noise analysis, expert systems, and noise knowledge bases. The low frequency (0.001 Hz to 1.0 Hz) behavior of PWR neutron noise is greatly affected by thermal-hydraulic feedback effects and the interrelated energy transport processes of the system. To describe the dynamic state of this complicated reactor system, a low-order whole-plant stochastic model was developed to account for the effects of feedback within the system. An expression for the neutron PSD was obtained by solving the model equations, made stochastic using the Langevin approach, for the Fourier transform of the normalized power fluctuations. Using the results of functional fits of the model to plant data, the response of the dynamic system to changes in important physical parameters was evaluated by a direct sensitivity analysis. In addition, the effect of such variations in the reactor condition on observable features in neutron noise descriptors was investigated. Based on the detection criteria used in current surveillance systems and the sensitivity results of this study, it was possible to relate changes in monitored spectra to changes in physical parameters of the dynamic reactor system and to determine detection thresholds. In the high frequency range (1 Hz to 20 Hz), PWR neutron noise is dominated by vibration peaks resulting from the motion of reactor internals. To allow a quantitative investigation of the resonance structure of a neutron PSD and its evolution during a fuel cycle, a resonance model was developed from perturbation theory to give the detector response for small in-core mechanical motions. By mathematically manipulating the model, an equation for the neutron PSD was obtained that describes each motion in terms of a pole-strength factor, a resonance asymmetry (or skewness) factor, a vibration damping factor, and a frequency of vibration. This formulation allows each resonance peak to be quantified in terms of four identifiable parameters. The mechanical motion parameters for several resonances were determined by a functional fit of the model to plant data taken at various times during a fuel cycle and were tracked to determine trends that indicated changes in vibrations within the reactor core. In addition, the resonance model gave the ability to separate the resonant components of the PSD after the parameters had been identified. As a result, the behavior of several vibration peaks were monitored over a fuel cycle.

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