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Imeni Vladimira Il’icha Lenina, Russia

Chepkasov I.V.,Katanov State University of Khakassia | Popov Z.I.,RAS Kirensky Institute of Physics
IOP Conference Series: Materials Science and Engineering | Year: 2015

Molecular dynamics method using the tight-binding potential to carry out simulation of ultrafast heating of the synthesized particles from the gas phase to a temperature T= 600K and T= 900K, at which the particles were kept about 10 ns. As a result of the simulation revealed that the method of ultrafast heating the particles to high temperatures virtually eliminates the possibility of a clusters of defective education, but as a result of the heat treatment, the some of investigated particles can disconnect (burst) into smaller clusters. © Published under licence by IOP Publishing Ltd. Source


Udodov V.N.,Katanov State University of Khakassia
Physics of the Solid State | Year: 2015

The general interpolation formulas, which generalize the classical consequences of the static scaling hypothesis for phase transitions with variation in the temperature and field, have been proposed. The classical results have been derived from these formulas as a limiting partial case for the asymptotic proximity to a positive critical temperature. It has also been shown that some consequences of the scaling hypothesis also remain correct at a zero critical temperature; however, for example, the Essam–Fisher equality changes its form in the latter case, namely, the numeral two on the right-hand side is replaced by unity. © 2015, Pleiades Publishing, Ltd. Source


Engel E.A.,Katanov State University of Khakassia | Kovalev I.V.,Siberian State Aerospace University | Engel N.E.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2016

An article describes vector control of wind turbine based on fuzzy selective neural net. Based on the wind turbine system's state, the fuzzy selective neural net tracks an maximum power point under random perturbations. Numerical simulations are accomplished to clarify the applicability and advantages of the proposed vector wind turbine's control on the basis of the fuzzy selective neuronet. The simulation results show that the proposed intelligent control of wind turbine achieves real-time control speed and competitive performance, as compared to a classical control model with PID controllers based on traditional maximum torque control strategy. © Published under licence by IOP Publishing Ltd. Source


Engel E.A.,Katanov State University of Khakassia | Kovalev I.V.,Siberian State Aerospace University | Engel N.E.,Katanov State University of Khakassia
IOP Conference Series: Materials Science and Engineering | Year: 2016

This paper presents the fuzzy recurrent neuronet for PV system's control. Based on the PV system's state, the fuzzy recurrent neural net tracks the maximum power point under random perturbations. The validity and advantages of the proposed intelligent control of PV system are demonstrated by numerical simulations. The simulation results show that the proposed intelligent control of PV system achieves real-time control speed and competitive performance, as compared to a classical control scheme on the basis of the perturbation & observation algorithm. © Published under licence by IOP Publishing Ltd. Source


Gafner Y.Y.,Katanov State University of Khakassia | Gafner S.L.,Katanov State University of Khakassia | Zamulin I.S.,Katanov State University of Khakassia | Redel L.V.,Katanov State University of Khakassia | Samsonov V.M.,Tver State University
Physics of the Solid State | Year: 2013

The problem of anomalously high experimental values of the heat capacity of metallic nanoclusters has been analyzed in terms of the thermodynamics of the surfaces, as well as based on the data of computer experiment. The heat capacity of ideal face-centered cubic (fcc) palladium clusters with a diameter of 6 nm in the temperature range of 150-300 K has been investigated using the molecular dynamics method with several tight-binding potentials. It has been found that, at a temperature T = 150 K, the heat capacity of a Pd nanoparticle exceeds the heat capacity of the bulk material by 12-16%. Based on the results of the theoretical treatment, computer simulation, and analysis of experimental data, it has been concluded that an increase in the heat capacity of the compacted nanomaterial is not determined by the high heat capacity of individual clusters. Apparently, the significant increase in the heat capacity of compact nanomaterials can be explained either by their disordered state or by the high content of different types of impurities, mainly hydrogen. © 2013 Pleiades Publishing, Ltd. Source

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