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  8. 38-1

Electronic Modeling

Vol 38, No 1 (2016)

https://doi.org/10.15407/emodel.38.01

CONTENTS

Mathematical Modeling and Computation Methods

  MELNYK I.V.
Estimation of Energy Efficiency of Pulsed High Voltage Glow Discharge Electron Sources with Allowance for the Processes on Electrodes and Parameters of Anode Plasma
3-18
  KRASILNIKOV A.I.
Models of Asymmetrical Distributions of Random Variables with Zero Asymmetry Coefficient
19-34
  KLEVTSOV Yu.A.
Structural Transformations of Systems with Distributed Parameters
35-46

Informational Technologies

  TIMCHENKO L.I., NAKONECHNAYA S.V., KOKRIATSKAYA N.I.
Information Technology of Classification of Spot Images of Laser Beams and Forecasting Coordinates of their Energy Centers Using Parallel-Hierarchical Networks
47-62
  OGIR O.S., TARAPATA V.V., CHEMERIS A.A., OGIR O.O.
System of Ultrasonic Diagnostics with the Use of Phase Information of Reflected Sound Field
63-72

Computational Processes and Systems

  KRAVTSOV H.A.
Model of Computations over Classifications
73-86
  SAPOZHNIKOV V.V., SAPOZHNIKOV Vl.V., EFANOV D.V., DMITRIEV V.V., CHEREPANOVA
M.R.
Organization of Combinational Circuits Concurrent Error Detection Systems Based on the Modified Code with Summation of Weighted Transitions
87-98

Application of Modeling Methods and Facilities

  ZHARKYN A.F., POPOV V.A. , BANUZADE SAHRAGARD S., ZAMKOVYI P.A., SPODYNSKA
A.V.
Multicriteria Evaluation of Alternative Options for the Distributed Generation Sources Integration Into the Distribution Networks
99-112
  LYSENKOV E.A., KLEPKO V.V.
Modelling of Electrical Conductivity of the Systems Based on Polyethers and Carbon Nanotubes
113-124

 

 

ESTIMATION OF ENERGY EFFICIENCY OF PULSED HIGH VOLTAGE GLOW DISCHARGE ELECTRON SOURCES WITH ALLOWANCE FOR THE PROCESSES ON ELECTRODES AND PARAMETERS OF ANODE PLASMA

I.V. Melnyk

Èlektron. model. 2018, 38(1):03-18
https://doi.org/10.15407/emodel.38.01.003

ABSTRACT

Methods of simulation of energy efficiency of pulsed electron sources of high voltage glow discharge are considered in the article. The proposed methods are based on the complex analysis of physical processes, taking place in the region of cathode potential drop and in the region of anode plasma of high voltage discharge. The obtained simulation results show, that energy efficiency of pulsed glow discharge electron sources depended on the parameters of additional discharge and
on relative control pulse duration ratio. With using suitable parameters of additional discharge the energy efficiency may exceed 90%.

KEYWORDS

electron-beam technologies, electron source, high voltage glow discharge, pulsed operation, energy efficiency.

REFERENCES

1. Ladokhin, S.V., Levitskiy, N.I., Chernyavsky, V.B. et al. (2007), Elektronno-luchevaya plavka v liteynom proizvodstve [Electron-beam melting in foundry], Stal, Kiev, Ukraine. 
2. Grechanyuk, M.I., Melnyk, A.G., Grechanyuk, I.M. et al. (2014), “Modern electron beam technologies and equipment for melting and physical vapor deposition of different materials”, Elektrotekhnika i Elektronika (E+E), Vol. 49, no. 5-6, pp. 115-121.
3. Mattausch, G., Zimmermann, B., Fietzke, F. et al. (2014), “Gas discharge electron sources – proven and novel tools for thin-film technologies”, Elektrotekhnika i Elektronika (E+E), Vol. 49, no. 5-6, pp. 183-195.
4. Feinaeugle, P., Mattausch, G., Schmidt, S. and Roegner, F.H. (2011), “A new generation of plasma-based electron beam sources with high power density as a novel tool for high-rate PVD”, Society of Vacuum Coaters, 54th Annual Technical Conference Proceedings, Chicago, 2011, pp. 202-209.
5. Yarmolich, D., Nozar, P., Gleizer, S. et al. (2011), “Characterization of deposited films and the electron beam generated in the pulsed plasma deposition gun”, Japanese Journal of Applied Physics, Vol. 50, 08JD03. 
6. Mattausch, G., Scheffel, B., Zywitzki, O. et al. (2012), “Technologies and tools for the plasma-activated EB high-rate deposition of zirconia”, Elektrotekhnika i Elektronika (E+E), Vol. 47, no. 5-6, pp. 152-158.
7. Melnyk, I.V. (2013), “Generalized methods of simulation of high voltage glow discharge triode electron sources”, Elektronnoe modelirovanie, Vol. 35, no. 4, pp. 93-107.
8. Denbnovetsky, S.V., Melnyk, V.I., Melnyk, I.V. and Tugay, B.A. (2003), “Model of control of glow discharge electron gun current for microelectronics production applications”, Proceedings of SPIE. Sixth International Conference on Material Science and Material Properties for Infrared Optoelectronics, Vol. 5065, pp. 64-76.
https://doi.org/10.1117/12.502174
9. Shiller, S., Geisig, U. and Panzer, S. (1980), Elektronno-luchevaya tekhnologiya [Electron-beam technology], Energiya, Moscow, Russia.
10. Rykalin, N.N., Zuev, I.V. and Uglov, A.A. (1978), Osnovy elektronno-luchevoi obrabotki materialov [Foundations of electron-beam treatment of materials], Mashinostroenie, Moscow, Russia.
11. Grechanyuk, N., Kucherenko, P., Grechanyuk, I. and Shpack, P. (2006), “Modern technologies and equipment for obtaining new materials and coatings”, Elektrotekhnika i Elektronika (E+E), Vol. 41, no. 5-6, pp. 122-128.
12. Pinto, T., Buxton, A., Neailey, K. and Barnes, S. (2014) “Surface engineer improvements and opportunities with electron beams”, Elektrotekhnika i Elektronika (E+E), Vol. 49, no. 5-6, pp. 221-225.
13. Melnyk, I.V. (2013), “Estimation of time of increasing of high voltage glow discharge electron current in the triode electrode system under supply of control impulse”, Izvestiya vuzov. Radioelektronika, Vol. 56, no. 12, pp. 51-61.
14. Melnyk, I.V. (2014), “Simulation of time of current increasing in impulse triode high voltage glow discharge electron guns”, Elektrotekhnika i Elektronika (E+E), Vol. 49, no. 5-6, pp. 254-258.
15. Melnyk, I.V. and Tugay, S.B. (2013), “Analytical calculation of plasma boundary position in high voltage glow discharge under the lighting of additional discharge”, Izvestiya vuzov. Radioelektronika, Vol. 55, no. 11, pp. 50-59.
16. Novikov, A.A. (1983), Istochniki elektronov vysokovoltnogo tleyuschego razryada s anodnoy plasmoy [High voltage glow discharge electron sources with anode plasma], Energoatomizdat, Moscow, Russia.
17. Zavialov, M.A., Kreyndel, Yu.E., Novikov, A.A. and Shanturin, L.P. (1989), Plasmennye processy v tekhnologicheskikh elektronnykh pushkakh [Plasma processes in technological electron guns], Atomizdat, Moscow, Russia.
18. Granovskiy, V.L. (1952), Elektricheskiy tok v gazakh. Tom 1. Obschie voprosy elektrodinamiki gazov [Electric current in gases. Vol. 1. General problems of gas electrodynamics], Gosudarstvennoe izdatelstvo fiziko-matematicheskoy literatury, Moscow, Leningrad, Russia.
19. Raizer, Yu.P. (1987), Fizika gazovogo razryada [Physics of gas discharge], Nauka, Moscow, Russia.

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MODELS OF ASYMMETRICAL DISTRIBUTIONS OF RANDOM VARIABLES WITH ZERO ASYMMETRY COEFFICIENT

A.I. Krasilnikov

Èlektron. model. 2018, 38(1):19-34
https://doi.org/10.15407/emodel.38.01.019

ABSTRACT

The use of mixtures of distributions for finding possible asymmetrical distributions with zero asymmetry coefficients has been substantiated as based on the method of randomization. Mathematical models of asymmetric distributions with zero asymmetry coefficients have been analyzed; the models were obtained by the randomization of the shift and scale parameters of the basic distribution function. The examples of finding such distributions are given. The obtained results
allow realizing the mathematical and computer modeling of asymmetric distributions with zero asymmetry coefficients.

KEYWORDS

asymmetric distributions, cumulant coefficients, coefficient of skewness, mixtures of distributions, conjugate distributions.

REFERENCES

1. Novitskii, P.V. and Zograf, I.A. (1991), Otsenka pogreshnostei rezultatov izmerenii [Error estimation in measurement results], Energoatomizdat, St. Petersburg, Russia.
2. Alexandrou, D., De Moustier, C. and Haralabus, G. (1992), “Evaluation and verification of bottom acoustic reverberation statistics predicted by the point scattering model”, J. Acoust. Soc. Am., Vol. 91, no. 3, pp. 1403-1413.
https://doi.org/10.1121/1.402471
3. Shelukhin, O.I. (1998), Negaussovskie protsessy v radiotekhnike [Non-Gaussian processes in radio engineering], Radio i svyaz, Moscow, Russia.
4. Marchenko, B.G., Matsiuk, O.V. and Fryz, M.Ye. (2005), Matematychni modeli y obrobka sygnaliv v oftalmolohii [Mathematical models and processing of signals in ophthalmology], Ternopil Ivan Pul’uj National Technical University, Ternopil, Ukraine.
5. Potapov, A.A., Gilmutdinov, A.Kh. and Ushakov, P.A. (2008), “System principles and element base of fractal radioelectronics. Part 2. Methods of synthesis, models and application prospect”, Radiotekhnika i elektronika, Vol. 53, no. 11, pp. 1347-1394.
6. Palagin, V.V. (2010), “Adaptation of moment quality criterion for the multiple-choice task of verification of hypotheses when using the polynomial decision rules”, Elektronnoe modelirovanie, Vol. 32, no. 4, pp. 17-33.
7. Krasilnikov, A.I. (2014), Modeli shumovykh signalov v sistemakh diagnostiki teploenergeticheskogo oborudovaniya [Models of noise signals in the systems of diagnostics of heatand-power producing equipment], Institute of Engineering Thermophysics of NAS of Ukraine, Kyiv, Ukraine.
8. Babak, S.V., Myslovich, M.V. and Sysak, R.M. (2015), Statisticheskaya diagnostika elektrotekhnicheskogo oborudovaniya [Statistical diagnostics of the electrotechnical equipment], Institute of Electrodynamics of NAS of Ukraine, Kyiv, Ukraine.
9. Bostandzhiyan, V.A. (2009), Raspredelenie Pirsona, Dzhonsona, Veibulla i obratnoe normalnoe. Otsenivanie ikh parametrov [Pearson, Johnson, Weibull distribution and the reverse normal. Estimation of their parameters], Institute for Problems of Chemical Physics of RAS, Chernogolovka, Russia.
10. Senatov, V.V. (2009), Tsentralnaya predelnaya teorema: Tochnost approksimatsii i asimptoticheskie razlozheniya [Central limit theorem: Approximation accuracy and asymptotic decompositions], Knizhnyi dom «Librokom», Moscow, Russia.
11. Korolev, V.Yu. (2004), Smeshannye gaussovskie veroyatnostnye modeli realnykh protsessov [ThemixedGaussian probabilisticmodels of real processes],Maks Press, Moscow,Russia.
12. Malakhov, A.N. (1978), Kumulyantnyi analiz sluchainykh negaussovykh protsessov i ikh preobrazovanii [Cumulant analysis of random non-Gaussian processes and their transformations], Sovetskoe radio, Moscow, Russia.
13. Kunchenko, Yu.P. (2001), Polinomialnye otsenki parametrov blizkikh k gaussovskim sluchainyh velichin. Ch. I. Stokhasticheskie polinomy, ikh svoistva i primenenie dlya nakhozhdeniya otsenok parametrov [Parameter polynomial estimations of random variables close to Gaussian. Part I. Stochastic polynomials, their properties and application for finding the parameter estimations], ChITI, Cherkassy, Ukraine.
14. De Carlo, L.T. (1997), “On the meaning and use of kurtosis”, Psychological Methods, Vol. 2, no. 3, pp. 292-307.
https://doi.org/10.1037/1082-989X.2.3.292
15. Kuznetsov, B.F., Borodkin, D.K. and Lebedeva, L.V. (2013), “Cumulant models of additional errors”, Sovremennye tekhnologii. Sistemnyi analiz.Modelirovanie, no. 1 (37), pp. 134-138.
16. Krasilnikov, A.I., (2002), “Poisson moments of infinitely divisible distributions”, Elektronika i svyaz, no. 15, pp. 84-88.
17. Marchenko, B.G. and Shcherbak, L.N. (1993), “Moment problem and cumulant analysis”, Otbor i obrabotka informatsii, Vol. 9 (85), pp. 12-20.
18. Krasilnikov, A.I. (2013), “Class of non-Gaussian distributions with zero skewness and kurtosis”, Izvestiia vysshikh uchebnykh zavedenii. Radioelektronika, Vol. 56, no. 6, pp. 56-63.
https://doi.org/10.3103/S0735272713060071
19. Jondeau, E. and Rockinger, M. (2001), “Gram-Charlier densities”, Journal of Economic Dynamics and Control, Vol. 25, pp. 1457-1483.
https://doi.org/10.1016/S0165-1889(99)00082-2
20. Jondeau, E. and Rockinger, M. (2003), “Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements”, Journal of Economic Dynamics and Control, Vol. 27, pp. 1699-1737.
21. Krasilnikov, A.I. and Pilipenko, K.P (2007), “Unimodal two-component Gaussian mixture. Excess kurtosis”, Elektronika i svyaz, no. 2 (37), pp. 32-38.
22. Chepynoha, A.V. (2010), “Areas of realization of bi-Gaussian models of skewness-excess random variables with the punched moment-cumulant description”, Visnyk ChDTU, no. 2, pp. 91-95.

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STRUCTURAL TRANSFORMATIONS OF SYSTEMS WITH DISTRIBUTED PARAMETERS

Yu.A. Klevtsov

Èlektron. model. 2018, 38(1):35-46
https://doi.org/10.15407/emodel.38.01.035

ABSTRACT

A class of models – transfer functions of three-dimensional systems with distributed parameters – has been considered on the basis of the theory of finite integrated transformations. The tasks of structural transformations have been solved. Examples of modeling the series and parallel connection of the two units are given.

KEYWORDS

finite integral transformations, systems with distributed parameters, transfer function, structural method.

REFERENCES

1. Butkovskiy, A.G. (1977), Strukturnaya teoriya raspredelennykh system [Structural theory of distributed systems], Nauka, Moscow, Russia.
2. Butkovskiy, A.G. (1979), Kharakteristiki sistem s raspredelennymi parametrami [Characteristics of distributed parameter systems], Nauka, Moscow, Russia.
3. Martynenko, N.A. and Pustylnikov, L.M. (1985), Konechnyie integralnyie preobrazovaniya i ikh primenenie k issledovaniyu sistem s raspredelennymi parametrami. Spravochnoe posobie [Finite integral transformations and their application to the study of the systems with distributed parameters. Reference Handbook], Nauka, Moscow, Russia.
4. Solodovnikov, V.V. and Semenov, V.V. (1974), Spektralnaya teoriya nestatsionarnykh sistem upravleniya [The spectral theory of non-stationary control systems], Nauka, Moscow, Russia.
5. Kraskevitch, V.Ye. and Klevtsov, Yu.A. (1985), “Spectral method in the problems of structural transformations of the objects with distributed parameters”, Izvestiya VUZov. Priborostroenie, Vol. 28, no. 6, pp. 9-13.
6. Klevtsov, Yu.A. (1988), “Spectral description of the objects with distributed parameters”, Elektronnoe modelirovanie, Vol. 10, no. 3, pp. 27-31.
7. Rapoport, E.Ya. (2003), Strukturnoe modelirovanie obektov i sistem upravleniya s raspredelennymi parametrami [Structural modeling of the objects and control systems with distributed parameters], Vysshaya shkola, Moscow, Russia.

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INFORMATION TECHNOLOGY OF CLASSIFICATION OF SPOT IMAGES OF LASER BEAMS AND FORECASTING COORDINATES OF THEIR ENERGY CENTERS USING PARALLEL-HIERARCHICAL NETWORKS

L.I. Timchenko, S.V. Nakonechnaya, N.I. Kokriatskaya

Èlektron. model. 2018, 38(1):47-62
https://doi.org/10.15407/emodel.38.01.047

ABSTRACT

The paper describes a method of forecasting the position of the energy center (EC) of the laser beam image using parallel-hierarchical networks. The basic steps for classification and forecasting of EC coordinate image spots of the laser beam, which gives the opportunity to develop new technology for the intelligent classification and prediction of coordinate position of their EC. The results of the comparative experimental evaluation of the prediction based on the known neural networks and the proposed method with the use of parallel-hierarchical network are presented.

KEYWORDS

forecasting, energy center, laser beam, parallel-hierarchical network, classification, preparation, neural networks.

REFERENCES

1. Chetyrkin, E.M. (1977), Statisticheskie metody prognozirovaniya [Statistical methods of forecasting], Statistika, Moscow, Russia.
2. Ghiassi, M., Saidane, H. and Zimbra, D.K. (2005), “A dynamic artificial neural network model for forecasting time series events”, International Journal of Forecasting, Vol. 21, no. 2, pp. 341-362.
3. Zhang, G., Patuwo, B.E. and Hu, M.Y. (1998), “Forecasting with artificial neural networks: the state of the art”, International Journal of Forecasting, Vol. 14, no. 1, pp. 35-62.
https://doi.org/10.1016/S0169-2070(97)00044-7
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5. Hill, T., Marquez, L., O’Connor, M. and Remus, W. (1994), “Artificial neural network models for forecasting and decision making”, International Journal of Forecasting, Vol. 10, no. 1, pp. 5-15.
6. Nakonechna, S., Petrovskyi, M., Timchenko, L., Kokryatskaya, N., Kutaev, Yu. and Yarovy, A. (2012), “A new approach to detection of noise-distorted signals based on the method of S-preparation”, IX International Symposium on Telecommunications, BIHTEL 2012, Sarajevo, Bosnia and Herzegovina, October 25-27, 2012, p. 6.
7. Nakonechna, S.V. (2012), “Method of S-preparation for correlative comparison of small objects”, Zbirnyk tez XLII Naukovo-praktychnoi konferentsii molodykh uchenykh, aspirantiv i studentiv «Zaliznychnyi transport: suchasni problemy nauky» [Proceedings of the XLII Scientific conference of students and young researchers. Railway transport: modern problems of science], Kyiv, DETUT, November 21, 2012, p. 237.
8. Timchenko, L.I., Nakonechnaya, S.V. and Yarovoy, A.A. (2014), “Parallel-hierarchical networks based on the cluster CPU-oriented hardware platform”, Sovremenny nauchny vestnik. Seriya: Sovremennye informatsionnye tekhnologii, Vol. 204, no. 8, pp. 50-56.
9. Timchenko, L.I. and Nakonechnaya, S.V. (2013), “Computer facilities to implement multilevel parallel-hierarchical networks based GPU-oriented hardware platform”, Zbirnyk naukovyh prats DETUT. Seriya: Transportni systemy i tekhnologii, Vol. 23, pp. 142-149.
10. Kormanovskyi, S.I. (2002), “Organization of homogeneous optoelectronic logical and temporal environments geometric analysis of the object”, Visnyk Vinnytskogo politekhnichnogo instytutu, no. 1, pp. 34-39.
11. Yarovoy, A.A. and Yarovoy, A.M. (2010), “Theoretical, methodological and practical aspects of the use of imaging technology for applications of laser beams profiling”, Elektronnyi zhurnal Natsionalnogo issledovatelskogo yadernogo universiteta “MIFI”, Nauchnaya vizualizatsiya, Vol. 2, no. 3, pp. 50-72.
12. Kozhemyako, V.P., Timchenko, L.I. and Yarovyi, A.A. (2006), “Methodological approaches to parallel-hierarchical processing laser beam spot images and their realization applied”, Optyko-elektronni informatsiyno-energetichni tekhnologii, Vol. 11, no. 1, pp. 14-25.
13. Abdrakhmanov, K.Sh., Bykova, O.G. and Ulanovskiy, M.V. (2010), “Standardization of measurement methods widths, divergence angles and beam propagation ratios of laser radiation (laser-beam divergence measurement)”, Metrologiya, no. 2, pp. 23-44.

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