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; Aoto, Kazumi;
JNC TN9400 99-061, 32 Pages, 1999/07
In this report, reconstruction of magnetic charges induced by mechanical damages in a test piece of SUS304 stainless steel is performed as a part of eforts to establish a passive nondestructive testing method on the basis of the inspection of leakage magnetic field. The approach for solving this typical ill-posed inverse problem is selected as a way in the least square method category. Concerning the ill-poseness of the system of equations, an iteration algorithm is adopted to its solving in which the designations of initial profile, the weight coefficients and the total number of iterations are taken as means of reqularization. From examples using simulated input data, it is verified that the approach gives good reconstruction results in case of signals with a relative high S/N ratio. For improving the robustness of the proposed method, a Galerkin procedure with base functions chosen as the Daubechies' wavelet is also introduced for discretizing the governing equation. By comparing the reconstruction results of the least square method and those using wavelet discretization, it is found that the wavelet used approach is more feasible in the inversion of noise polluted signals. Reconstruction of 1-D and 2-D magnetic charges with the least square strategy and reconstruction of an 1-D problem with the wavelet used method are carried out from both simulated and measured magnetic field signals which are used as the validation of the proposed inversion strategy.
Yang Jin An*;
JNC TN9400 99-013, 89 Pages, 1998/12
This report presents a variance reduction technique to estimate the reliability and availability of highly complex systems during phased mission time using the Monte Carlo simulation. In this study, we introduced the variance reduction technique with a concept of distance between the present system state and the cut set configurations. Using this technique, it becomes possible to bias the tansition from the operating states to the failed states of components towards the closest cut set. Therefore a component failure can drive the system towards a cut set configuration more effectively. JNC developed the PHAMMON (Phased Mission Analysis Program with Monte Carlo Method) code which involved the two kinds of variance reduction techniques : (1) forced transition, and (2)failure biasing. However, these techniques did not guarantee an effective reduction in variance. For further improvement, a variance reduction technique incorporating the distance concept was introduced to the PHAMMON code and the numerical calculation was carried out for the different design cases of decay heat removal system in a large fast breeder reactor. Our results indicate that the technique addition of this incorporating distance concept is an effective means of further reducing the variance.
Ugolini; Yoshikawa, Shinji; Ozawa, Kenji
PNC TN9410 95-210, 11 Pages, 1995/09
The proper control of the outlet steam temperature of the evaporator is of major importance for improving the overall performance of the balance of plant of a nuclear power reactor. This report presents a predictive and an anticipatory control algorithms based on the artificial neural network (ANN) technique. The two control algorithms are embedded on a model reference adaptive control system based on the ANN technique, defined as MRAC
. It has already been illustrated that nonlinear dynamical systems such as the evaporator of a nuclear power plant can be controlled by an MRAC system. However, little attention has been devoted on exploiting the forecasting potential of the ANN technique for enhancing the accuracy and improving the efficacy of the control action of the MRAC system. The improved MRAC system has been tested to simulate the behavior of a fast breeder reactor (FBR) evaporator and to control its outlet steam temperature. The simulation results indicate that the performance of the MRAC system substantially improves when the predictive and the anticipatory control algorithms are activated.
