Numerical Simulation of Measurements during the Reactor Physical Startup at Unit 3 of Rostov NPP

The results of numerical calculations and measurements of some reactor parameters during the physical startup tests at unit 3 of Rostov NPP are presented. The following parameters are considered: the critical boron acid concentration and the currents from ionization chambers (IC) during the scram system efficiency evaluation. The scram system efficiency was determined using the inverse point kinetics equation with the measured and simulated IC currents. The results of steady-state calculations of relative power distribution and efficiency of the scram system and separate groups of control rods of the control and protection system are also presented. The calculations are performed using several codes, including precision ones.     

Calculation of reactivities using ionization chamber currents with different sets of kinetic parameters for reduced scram system efficiency in the VVER-1000 of the third unit of the Kalinin nuclear power plant at the stage of physical start-up

The effectiveness of the VVER-1000 reactor scram system is analyzed using ionization chamber currents with different sets of kinetic parameters with allowance for the isotopic composition in the calculation of these parameters. The most “correct, aesthetically acceptable” results are obtained using the eight-group constants of the ROSFOND (BNAB-RF) library. The difference between the maximum and minimum values of the scram system effectiveness calculated with different sets of kinetic parameters slightly exceeds 2β. The problems of introducing corrections due to spatial effects are not considered in this study.     

A neural-network method for the synthesis of informative features for the classification of signal sources in cognitive radio systems

This paper discusses possible methods for the synthesis of informative features for the classification of signal sources in cognitive radio systems using artificial neural networks. A synthesis method based on the use of autoassociative neural networks is proposed. From the point of view of the classification of the signals, informativeness of synthesized features is estimated using a modified artificial neural network based on radial basis functions that contains an additional self-organizing layer of neurons that provide the automatic selection of the variance of basis functions and a significant reduction of the network dimension. It is shown that the use of autoassociative networks in the problem of the classification of signal sources makes it possible to synthesize the feature space with a minimum dimension while maintaining separation properties.     

Reactivity effects in VVER-1000 of the third unit of the kalinin nuclear power plant at physical start-up. Computations in ShIPR intellectual code system with library of two-group cross sections generated by UNK code

The ShIPR intellectual code system for mathematical simulation of nuclear reactors includes a set of computing modules implementing the preparation of macro cross sections on the basis of the two-group library of neutron-physics cross sections obtained for the SKETCH-N nodal code. This library is created by using the UNK code for 3D diffusion computation of first VVER-1000 fuel loadings. Computation of neutron fields in the ShIPR system is performed using the DP3 code in the two-group diffusion approximation in 3D triangular geometry. The efficiency of all groups of control rods for the first fuel loading of the third unit of the Kalinin Nuclear Power Plant is computed. The temperature, barometric, and density effects of reactivity as well as the reactivity coefficient due to the concentration of boric acid in the reactor were computed additionally. Results of computations are compared with the experiment.     

Methods for the automatic recognition of digital modulation of signals in cognitive radio systems

This paper considers one of the problematic issues of creating radio systems based on cognitive radio technology, viz., automatic recognition of the digital-modulation formats of radio signals. In accordance with the recommendations of the E2R and the European Telecommunications Standards Institute (ETSI) consortium, cognitive radio systems have the ability to modulate/demodulate signals in all frequency bands and in all modes of modulation. This process should be performed automatically, according to the current technical capabilities of the available communication system, the requirements for the quality of communication, and different external conditions. This article provides an analysis of the promising methods of automatic recognition of digitally modulated radio signal formats, viz., using the shape of the phase constellation, using the distribution difference of instantaneous phases, and using high-order cumulants. According to the results of the analysis, we propose methods of recognition that are based on cumulant analysis for cognitive radio systems. It is proposed that the decision-making device be an artificial neural network.     

Detection of Terahertz,Mid- and Near Infrared Radiation by a Multilayer Metal—Insulator Heterostructure

An analogy between the tunneling of quantum particles through a chain of barriers and the propagation of electromagnetic waves through a metamedium has allowed new methods for the fabrication of selective detectors of terahertz, mid-infrared, and near infrared radiation. The calculations have shown that a resonance metal-insulator heterostructure with one and two metal layers allows achieving nearly 100% absorption of radiation in a narrow frequency range. The use of a large number of metal layers makes it possible to detect ultrashort (including picosecond) field pulses with a broad spectrum.