05 Nuclear fuels (scientific, technical)

05/00998 Application of a nonlinear dynamical descriptor to BWR stability analyses Suzudo, T. et al. Progress in Nuclear Energy, 2003, 43, (1-4), 217-223. Reactor noise analysis method based on non-linear dynamical theory is applied to the Forsmarks l&2 BWR stability benchmark organized by OECD/NEA. The method utilizes the determination process of the fractal dimension of oscillatory neutron-flux signals. For practical application, the fractal dimension is expected to classify different asymptotic regimes of non-linear dynamical systems. In this case, each signal is classified into stable, quasi-stable, and unstable states. It was confirmed that the result was consistent to that of decay ratios. In addition, because the data processing does not include fitting calculation often used by the decay ratio, it is surmised that the result hardly varies with analysers. This can be the prominent advantage of this methodology compared to decay ratio.

05100999 Application of advanced core process monitoring procedures in German power reactors Pohlus, J. Progress in Nuclear Energy, 2003, 43, (1-4), 27-34. The nuclear reactor core design and the nuclear fuel management have been changed remarkable during the last few years. This development was initiated by increasing costs for the fuel recycling and nuclear waste storage. The fuel material, the fuel pellet fabrication, the fuel assembly structure and the core composition have been varied to get an effective fuel exploitation. Based on advanced core process conditions the reactor power and the fuel burn-up have been increased at German plants in recent years. Improved dynamic process monitoring pro- cedures are required to get more information about the varied core process behaviour during the reactor operation. Since several years ISTec has been performed investigations to the process monitoring based on process signal measurements in German nuclear power plants. Using the standard instrumentation of the plants process signals have been measured and analysed by means of the digital data acquisition system SIGMA. The measured time signals are influenced by core process transients, global and local process fluctuations and by signal line transfer functions. Advanced time series analysis methods have been applied to separate different process effects in the multiple signal matrix. The separation of different process influences can improve significantly the information about the process condition in the reactor core.

05/01000 Application of global optimization to VVER-1000 reactor diagnostics Kinelev, V. G. et al. Progress in Nuclear Energy, 2003, 43, (1-4), 51 56. Problems of reactor equipment diagnostics are formulated as inverse eigenvalue problems. Numerical methods of solving the inverse problems are presented. Incompleteness of spectral data results in the error function being non-convex. As the function has numerous local minima, it is necessary to use global optimization methods. Two different strategies are discussed: the modified TRUST algorithm and the algorithm that reduces the original problem to a one-dimensional form. The outcome algorithm that combines the strategies is proposed. Results of computational experiments are presented to illustrate the efficiency of the approach.

05•01001 Assessment of linear and non-linear autoregressive methods for BWR stability monitoring Manera, A. et al. Progress in Nuclear Energy, 2003, 43, (1-4), 321 327. A benchmark has been performed to compare the performances of exponential autoregressive (ExpAR) models against linear autoregres- sive (AR) models with respect to boiling water reactor stability monitoring. The well-known March-Leuba reduced-order model is used to generate the time-series to be analysed, since this model is able to reproduce the most significant non-linear behaviour of boiling water reactors (i.e. converging, diverging and limit-cycle oscillations). In this way the stability characteristics of the signals to be analysed are known a priori. An application to experimental time-traces measured on a thermalhydraulic natural circulation loop is reported as well. All methods perform equally well in determining the stability character- istics of the analysed signals.

05/01002 Comparisons between the various types of neural networks with the data of wide range operational conditions of the Borssele NPP Ayaz, E. et al. Progress in Nuclear Energy, 2003, 43, (1-4), 381-387. This paper addresses a trend monitoring in operating nuclear power plant by use of two types of Recurrent Neural Networks (RNN). The interesting feature of the RNN is intrinsic dynamic memory that reflects the current output as well as the previous inputs and outputs are gradually quenched. The first one Elman type of R NN which has a feed-back from hidden layer to the input layer neurons while in the Jordan type, from the outputs of the neural net to the inputs of the neural net. In this paper the theoretical assessment of the both RNNs is given. Both topological structures including Back Propagation (BP) neural network were implemented to the Borssele NPP. Learning

achieved from 30% to 100% nominal power at the starting period of the new core 30 September 2001. After learning period the reactor operation is followed by the neural network. Paper will present the reactor system, the real time data collection and the merits of the three types of the neural network applied while in the learning and continuous processing of the changing of the operational conditions.

05/01003 Development and application of core diagnostics and monitoring for the Ringhals PWRS Andersson, T. et al. Progress in Nuclear Energy, 2003, 43, (1-4), 35-41. Noise analysis and reactor diagnostics have been applied at the Ringhals PWRs for a long time. Through a collaboration with the Department of Reactor Physics, Chalmers University of Technology, methods for treating new problems were elaborated, and known methods were developed further to make them more effective or to suit specific applications. All these methods were tested in real measure- ments, and many of them have been used routinely afterwards. In this paper two particular new methods are described in detail: (1) the determination of the axial position of control rods from the axial shape of the neutron flux with neural network methods, and (2) the use of gamma thermometers for the determination of the MTC and for core flow estimation.

05/01004 Development of a BWR loading pattern design system based on modified genetic algorithms and knowledge Martfn-del-Campo, C. et al. Annals of Nuclear Energy, 2004, 31, (16), 1901-1911. An optimization system based on Genetic Algorithms (GAs), in combination with expert knowledge coded in heuristics rules, was developed for the design of optimized boiling water reactor (BWR) fuel loading patterns. The system was coded in a computer program named Loading Pattern Optimization System based on Genetic Algorithms, in which the optimization code uses GAs to select candidate solutions, and the core simulator code CM-PRESTO to evaluate them. A multi-objective function was built to maximize the cycle energy length while satisfying power and reactivity constraints used as BWR design parameters. Heuristic rules were applied to satisfy standard fuel management recommendations as the Control Cell Core and Low Leakage loading strategies, and octant symmetry. To test the system performance, an optimized cycle was designed and compared against an actual operating cycle of Laguna Verde Nuclear Power Plant, Unit I.

05/01005 Development of integrated automatic diagnosis method for loose parts monitoring system Kim, J.-S. el al. Progress in Nuclear Energy, 2003, 43, (1-4), 233-242. Generally, it is known that loose parts in the reactor coolant systems (RCS) bring serious damage into the system components and impede the normal function of the system. So, it is necessary to rapidly respond when the impact event has occurred. This paper presents a realization of automatic diagnosis algorithm for LPMS (Loose Parts Monitoring System) and application results to the impact test data at YongGwang Nuclear Power Plant Unit 3 (YGN3), Kori Nuclear Power Plant Unit 4 (KNU4) and the real data at YongGwang Nuclear Power Plant Unit 1 (YGN1). The integrated diagnosis algorithm is composed of three parts; pre-filtering, impact location and mass estimation. The pre- filtering is needed to reject low frequency background noises. To estimate the impact location, the starting points of impact are detected from the filtered signals and compared to produce the time differences, and then the modified triangular method is applied. To estimate the mass and energy of a loose part, the maximum amplitude and the initial half period were automatically computed. Additionally, a modified impact theory considering amplitude and energy attenuation effects was applied. To show the effectiveness of the proposed diagnostic method, the real impact test data at YGN3, KNU4 and the real impact data at YGN 1 was used. The analysis results show that the location estimation error is on average below 7.5%, and the average mass estimation is within 40%.

05/01006 Development of microphone leak detection technology on Fugen NPP Shimanskiy, S. et al. Progress in Nuclear Energy, 2003, 43, (1-4), 357- 364. A method of leak detection, based on high-temperature resistant microphones, was originally developed in JNC to detect leakages with flow rates from 1 m~h to 500m3/h. The development performed on Fugen is focused on detection of a small leakage at an early stage. Specifically, for the inlet feeder pipes the leak rate of 0.2gpm (0.046m3/ h) has been chosen as a target detection capability. Evaluation of detection sensitivity was carried out in order to check the capability of the method to satisfy this requirement. The possibility of detecting and locating a small leakage has been demonstrated through the research.

154 Fuel and Energy Abstracts May 2005