2. Home
  3. ARCHIVE
  4. 2020
  5. VOL 42, NO 3 (2020)
  6. pp. 53-70

COMPUTER MODELS FOR MODE CONTROL OF ELECTRIC CURRENT TREATMENT OF MELTS AT SPECIFIED QUALITY CRITERIA FOR CAST PRODUCTS. PART 1.

Yu.M. Zaporozhets, A.V. Ivanov, Yu.P. Kondratenko, V.M. Tsurkin

Èlektron. model. 2020, 42(3):53-69
https://doi.org/10.15407/emodel.42.03.053

ABSTRACT

The possibility of modes control of electric current treatment (MCECT) is justified. It is shown that features of multifactor influence of control parameters in the process of melt treatment on castings structural formation can be revealed only by numerical experiments with the help of adequate computer models. The main principles of construction of the automated system of MCECT are formulated and the structure of the integrated three-component information system (ITIS) for its realization by means of computer models of ECT multiphysical processes is developed. Computer models serve as the system base of the algorithmic paradigm embedded in ITIS, which includes the identification of experimental samples of castings with standard prototypes and prognostic algorithms for the modes controlling of electric current melt processing.

KEYWORDS

casting, quality, electric current treatment, mode, control, information system, computer model, algorithm.

REFERENCES

  1. Tsurkin, V.N. (2008), “Cast metal quality management concepts”, Metal and casting of Ukraine, no. 9, pp. 25–28.
  2. Gerasimov, V.G., Kliuev, V.V., Shaternikov V.E. (1985), Metody i pribory elektromagnitnogo kontrolya promyshlennyh izdelij [Methods and tools for electromagnetic testing of industrial products], Moscow, Russia, Energoatomizdat.
  3. Dobrzańsk, L.A., Krupiński, M. and Sokolowski, J.H. (2007), “Methodology of automatic quality control of aluminium castings”, Jour. Achiev. Mater. Manuf. Eng. (JAMME), Vol. 20, no. 1-2, рp. 69 – 78.
  4. Świłło, S.J., Perzyk, M. (2013). “Surface Casting Defects Inspection Using Vision System and Neural Network Techniques” , Arch. Foundry Eng. 2013, Vol. 13, no. 4, pp. 103 – 106.
    https://doi.org/10.2478/afe-2013-0091
  5. Birkhold, M., Friedrich, C. and Lechler, A. (2015), “Automation of the Casting Process using a model-based NC Architecture”, Science Direct, 2015, Papers Online 48-17, рр.195–200.
    https://doi.org/10.1016/j.ifacol.2015.10.102
  6. Frank Herold, Rolf-Rainer Grigat, Klaus Bavendiek (2002), “A New Analysis and Classification Method for Automatic Defect Recognition in X-Ray Images of Castings”, NDT.net, 2002, 10, (7), available at: https://www.ndt.net/article/ecndt02/207/207.htm.
  7. Nikitin, K. V., Nikitin, V. I., Timoshkin, I. Yu. et al. (2014), “Hereditary influence of the structure of charge materials on the density of aluminum alloys of the Al-Si system”, Izvestiya Vuzov. Tsvetnaya Metallurgiya (Universities' Proceedings Non-Ferrous Metallurgy), 6, pp. 22 – 27; 
    https://doi.org/10.17073/0021-3438-2014-6-22-27
  8. Tsurkin, V.N., Sinchuk, A.V., Ivanov, A.V. (2011) “Electric current treatment of liquid and crystallizing alloys in casting technologies”, Eng. Appl. Electrochem., Vol. 46, no. 5, pp. 456–464.
    https://doi.org/10.3103/S1068375511050115
  9. Ban, C., Han, Y., Ba, Q. et al. (2007), “Influence of pulse electric current on solidification structure of Al-Sn alloy”, Electromagn. Process. Mater., no. 8, pp. 34–37.
  10. He Lijia, Wang Jianzhong, Qi Jingang, Du Huiling and Zhao Zuofu (2010), “Influences of electric pulse on solidification structure of LM-29 Al-Si alloy”, Сhina Foundry, Vol. 7, no.2, pp. 153 – 156.
  11. Zhang, Y., Song, C., Zhu L. et al. (2011), “Influence of Electric-Current Pulse Treatment on the Formation of Regular Eutectic Morphology in an Al-Si Eutectic Alloy”, Mater. Trans., Vol. 42, pp. 604–611  
    https://doi.org/10.1007/s11663-011-9502-9
  12. Jingang Qi, Yang Li, Tukur S.A. et al. (2014), “A model study for the electric pulse frequency effects on the solidification behavior of Al-5%Сu alloy”, Intern. Journal of Scientific & Technology Research, Vol 3, no. 9, pр. 267–274.
  13. Nakada, M., Shiohara, Y., Flemings, M.C. (1990), “Modification of solidification structures by pulse electric discharging” ISIJ Int., Vol 30, pp. 27–33.
    https://doi.org/10.2355/isijinternational.30.27
  14. Ivanov, A.V., Sinchuk, A.V., Ruban, A.S. (2012), “Effect of the Technological Parameters of the Melt Treatment by a Electric Pulse Current on the Mixing Process”, Surf. Eng. Appl. Electrochem., 2012, Vol. 48, no. 2, pр. 180–186.
    https://doi.org/10.3103/S106837551202007X
  15. Zhang, Y. H., Xu, Y. Y., Ye, C. Y. et al. (2018), “Relevance of electrical current distribution to the forced fow and grain refnement in solidifed Al-Si hypoeutectic alloy”, Scientific Reports, 8:3242 | DOI: 0.1038/ s41598-018-21709-y.
  16. Eskin, D.G., Mi, J. (2019) Solidification Processing of Metallic Alloys under External Fields, Springer, Berlin/Heidelberg, Germany.
    https://doi.org/10.1007/978-3-319-94842-3
  17. Ivanov, A.V., Tsurkin, V.N. (2018), “Peculiarities of Distribution of Electromagnetic and Hydrodynamic Fields for Conductive Electric Current Treatment of Melts in Different Modes”, Surf. Eng. Appl. Electrochem, 2018, Vol. 55, no. 1, pр. 53–64.
    https://doi.org/10.3103/S1068375519010101
  18. Yuriy Zaporozhets, Artem Ivanov, Yuriy Kondratenko (2019), “Geometrical Platform of Big Database Computing for Modeling of Complex Physical Phenomena in Electric Current Treatment of Liquid Metals”, Data, 4, Issue 4;
    https://doi.org/10.3390/data4040136
  19. Kol’cov, D.A. (2006), Metody analiza i identifikacii neopredelennyh modelej eksperimenta [Methods of analysis and identification of uncertain experimental models], Avtoref. disser. …kand. fiz.-mat. nauk. Moscow.
  20. Kondratenko, Y.P., Joachim Rudolph, Kozlov, O.V., Zaporozhets, Y.M., Gerasin, O.S. (2017), “Neuro-fuzzy observers of clamping force for magnetically operated movers of mobile robots”, Tekhnichna Elektrodynamika [Technical Electrodynamics], no. 5, pp. 53 – 61.
    https://doi.org/10.15407/techned2017.05.053
  21. Yakunin, Ye.A (2012), “Mathematical simulation of crystallization process in application to prognostication of structure of hard-tempered from the liquid state metals”, State Higher Educational Institution “National Mining University”, 3, pp. 63 – 67.
  22. Farrokhnejad Mehdi (2013), Numerical Modeling of Solidification Process and Prediction of Mechanical Properties in Magnesium Alloys, Electronic Thesis and Dissertation Repository, 1459, available at: https:// ir.lib.uwo.ca/etd/1459.
  23. Andrushevich, A.A et al. (2012), Atlas mikrostruktur chernyh i cvetnyh metallov i splavov: ucheb. posobie [Atlas of microstructures of ferrous and non-ferrous metals and alloys: textbook], Minsk, Belarus.
  24. Nikrityuk, P.A., Eckert, K., Grundmann, R. (2005), “Numerical study of the influence of an applied electrical potential on the solidification of a binary metal alloy”, Wiley Online Library, 2-nd Sino-German Workshop on Electromagnetic Processing of Materials, Dresden, Germany, available at:
    https://doi.org/10.1002/9783527607969.ch41
  25. Jianzheng Guo and Mark Samonds (2011), “Simulation of Casting and Solidification Pro­cesses” The journal of the Minerals, Metals & Materials Society
    https://doi.org/10.1007/s11837-011-0104-4
  26. Povodator, A. M., Konashkov, V. V., Tcepelev, V. C., V’yuhin, V. V. (2012), “Study on the high-temperature melts properties through the use of correlation analysis”, Izvestiya vuzov. Chernaya metallurgiya,Vol. 55, no. 2, pp. 18–
    https://doi.org/10.17073/0368-0797-2012-2-18-21
  27. Manjunath Patel, Robins Mathew, Prasad Krishna, Mahesh B. Parappagoudar (2014), “Investigation of squeeze cast process parameters effects on secondary dendrite arm spacing using statistical regression and artificial neural network models”, ScienceDirect, Procedia Technology, Vol. 14, рp. 149 – 156.
    https://doi.org/10.1016/j.protcy.2014.08.020
  28. Fedin, S. S. (2010), “Adaptive neyrosetevaya model of prognostication and quality
    of multistage technological processes management”, Energy saving-Power engineering-Energy audit, 4 (74), c. 62 – 70.
  29. Nastac, L., Zhang, D. (2014), “3D Stochastic Modeling of Microstructure Evolution During the Solidification of Dendritic Alloys”, 2nd International Congress on 3D Materials Science, TMS, pp. 17-18 
    https://doi.org/10.1007/978-3-319-48123-4_3
  30. Zhu, M.F., Hong, C.P., Stefanescu, D.M. and Chang, Y.A. (2007), “Computational Modeling of Microstructure Evolution in Solidification of Aluminum Alloys”, Metallurgical and Materials  Transactions B Vol. 38B, рp. 517 –  524 
    https://doi.org/10.1007/s11663-007-9052-3

Full text: PDF