Temporal evolution of temperature and density profiles of a laser compressed core

Ochi, Yoshihiro; Golovkin, I.*; Mancini, R.*; Uschmann, I.*; Sunahara, Atsushi*; Nishimura, Hiroaki*; Fujita, Kazuhisa*; Louis, S.*; Nakai, Mitsuo*; Shiraga, Hiroyuki*; et al.

Review of Scientific Instruments, 74(3), p.1683 - 1687, 2003/03

https://doi.org/10.1063/1.1534389

no abstracts in English

R&D Study on on-line criticality surveillance system (IV)

Yamada, Susumu*

JNC TJ8400 2000-051, 122 Pages, 2000/02

JNC-TJ8400-2000-051.pdf:2.15MB

Developing an inexpensive on-line criticality surveillance system is required for ensuring the safety of nuclear fuel reprocessing plants. Based on the series of researches for five years, R&D study on On-line Criticality Surveillance System has been carricd out since 1996. The concept of this Criticality Surveillance System is based on the Auto-Regressive Moving Average (ARMA) model identification algorithms to the time series of signal fluctuation of a neutron detector. We have proposed several new ideas of modification to the original design of the Criticality Surveillance System, and also reported some results of numerical analysis over the DCA experiments. In those days, DOS/V personal computers with Microsoft Windows have came into wide use instead of those based on the MS-DOS, which have been popular in Japan. NEC, a major maker of MS-DOS computers, stopped the production of MS-DOS computers and changed their management policy toward production of DOS/V personal computers. Our researches have been developed using MS-DOS computers. For the effective use of these important results, it became an urgent theme to transplant all programs developed on MS_DOS computers into computers with the OS, which is not easily affected by commercialism. Since the design concept should be based on high reliability, electromagnetic disturbance-free and high expandability, and also computers have achieved remarkably high performance as well as low price in these days, these computers should be used not only as a simple signal processing unit but also a totally integrated signal analyzing system along with conventional signal analyzing software in stead of IC chips with analyzing soft wares. This configuration enables us to easily introduce newly developed techniques and to provide supplement information. Then, this approach can enhance the reliability of the Criticality Surveillance System without addition of any special devices, and also provide the flexibility of ...

Passive electromagnetic NED for mechanical damage inspection by detecting leakage magnetic flux, 1; Reconstruction of magnetic charges from detected field signals

; Aoto, Kazumi;

JNC TN9400 99-061, 32 Pages, 1999/07

JNC-TN9400-99-061.pdf:0.95MB

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.

Discrete Fracture Network Code Development; Heisei-10 progress report

Dershowitz, W.*; Doe, T.*; Shuttle, D.*; Eiben, T.*; Fox, A.*; Emsley, S.*; Ahlstrom, E.*

JNC TJ1400 99-012, 582 Pages, 1999/02

JNC-TJ1400-99-012.pdf:55.26MB

None

Development of Phased Mission Analysis Program with Monte Carlo Method - Improvement of the variance reduction technique with biasing towards top event -

Yang Jin An*;

JNC TN9400 99-013, 89 Pages, 1998/12

JNC-TN9400-99-013.pdf:2.0MB

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.

Studies on learning by detectiong impasse and by resuling it for building large scale knowledge base for autonomous plant

*

PNC TJ9604 98-001, 83 Pages, 1997/03

PNC-TJ9604-98-001.pdf:4.54MB

Recently, due to the tremendous improvement of information infrastructures such as networking facilities, the idea of a large scale knowledge base with realtime operations for technological plants has emerged. The major bottleneck for building a large scale knowledge base for an autonomous plant lies in its design phase. The acquisition of knowledge from human experts in an exhaustive way is extremely difficult, and even if it were possible, the maintenance of such a large knowledge base for realtime operation is not an easy task. The autonomous system having just incomplete knowledge would face with so many problems that contradicts with the system's current beliefs and/or are novel or unknown to the system. Experienced humans can manage to do with such novelty due to their generalizing ability and analogical inference based on the repertoire of precedents, even if they with new problems. Moreover, through experiencing such breakdowns and impasse, they can acquire some novel knowledge by their proactive attempts to interpret a provided problem as well as by updating their beliefs and contents and organization of their prior knowledge. We call such a style of learning as impasse-driven learning, meaning that learning dose occur being motivated by facing with contradiction and impasse. The related studies concerning with such a style of learning have been studied within a field of machine learning of artificial intelligence so far as well as within a cognitive science field. In this paper, we at first summarize an outline of machine learning methodologies, and then, we detail about the impasse-driven learning. We discuss that from two different perspectives of learning, one is from deductive and analogical learning and the other one is from inductive conceptual learning (i.e., concept formation or generalization-based memory). The former mainly discuss about how the learning system updates its prior beiiefs and knowledge so that it can explain away the ...

Sensor algorithms of the plasma vertical position to avoid a vertical displacement event during plasma-current quench on JT-60U

Yoshino, Ryuji; Koga, J. K.*; Takeda, Tatsuoki

Fusion Technology, 30(2), p.237 - 250, 1996/11

no abstracts in English

None

*; Nagasaki, Shinya*

PNC TJ1602 96-001, 67 Pages, 1996/03

PNC-TJ1602-96-001.pdf:1.42MB

None

Neural Network Predictive and Anticipatory Control Algorithms for a Neural Adaptive Control System

Ugolini; Yoshikawa, Shinji; Ozawa, Kenji

PNC TN9410 95-210, 11 Pages, 1995/09

PNC-TN9410-95-210.pdf:0.47MB

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.

None

Neyama, Atsushi*; Nakagawa, Koichi*; *; *

PNC TJ1458 95-004, 22 Pages, 1995/03

PNC-TJ1458-95-004.pdf:0.48MB

None