Prediction of Defects in the Structure of Non-Metallic Heterogeneous Materials | Journal of Engineering Sciences

Prediction of Defects in the Structure of Non-Metallic Heterogeneous Materials

Author(s): Tonkonogyi V.1, Holofieieva M.1*, Holofieiev Y.1, Klimov S.1, Naumenko Y.1, Dašić P.2

Affiliation(s):
1 Odesa Polytechnic National University, 1, Shevchenka Ave., 65044 Odesa, Ukraine;
2 Academy of Professional Studies Sumadija Department in Trstenik, 8, Kosovska St., 34000 Kragujevac, Serbia

*Corresponding Author’s Address: [email protected]

Issue: Volume 10, Issue 2 (2023)

Dates:
Submitted: June 29, 2023
Received in revised form: September 7, 2023
Accepted for publication: September 11, 2023
Available online: September 15, 2023

Citation:
Tonkonogyi V., Holofieieva M., Holofieiev Y., Klimov S., Naumenko Y., Dašić P. (2023). Prediction of defects in the structure of non-metallic heterogeneous materials. Journal of Engineering Sciences (Ukraine), Vol. 10(2), pp. C19–C25. DOI: 10.21272/jes.2023.10(2).c3

DOI: 10.21272/jes.2023.10(2).c3

Research Area:  MANUFACTURING ENGINEERING: Materials Science

Abstract. Heterogeneous media can be represented as specially organized heterogeneous materials. The complex process of forming heterogeneous materials and media as systems is realized by gradually transitioning from one state to another. The presence of many one-time transformations of space-time structures causes the latter. When simulating damage such as cracks and fractures in products made of non-metallic heterogeneous materials, which consists of “assigning” the place of damage to the product at a specific moment in time, neither the method of random selection from the previously compiled list of “dangerous” places, nor the method of transfer to the object can be used, which is modeled, the results of field and operational tests of other products of a similar class or even other products of the same class. Therefore, it is proposed to use a combined method of obtaining a stream of quasi-random numbers, that is, a stream of random numbers that are “modulated” by information about defects in the structure of the material of the product, which was obtained because of field tests of the products or during their operation.

Keywords: heterogeneous system, flaw detection, control method, defects prediction.

References:

  1. Tonkonogyi, V., Stanovskyi, O., Holofieieva, M., Levynskyi, O., Klimov, S. (2023). Vibration infrared thermal method of defectoscopy of non-metallic heterogeneous materials. In: Karabegovic, I., Kovačević, A., Mandzuka, S. (eds) New Technologies, Development and Application VI. NT 2023. Lecture Notes in Networks and Systems, Vol 687. Springer, Cham. https://doi.org/10.1007/978-3-031-31066-9_33
  2. Chappard, D., Degasne, I., Hure, G., Legrand, E., Audran, M., Basle, M. F. (2003). Image analysis measurements of roughness by texture and fractal analysis correlate with contact profilometry. Biomaterials, Vol. 8, pp. 1399–1407. https://doi.org/10.1016/S0142-9612(02)00524-0
  3. Gholizadeh, S. (2016). A review of non-destructive testing methods of composite materials. Procedia Structural Integrity, Vol. 1, pp 50–57. https://doi.org/10.1016/j.prostr.2016.02.008
  4. Larsson, C., Thomsen, P., Lausmaa, J., Rodahl, M., Kasemo, B., Ericson, L. E. (1994). Bone response to surface modified titanium implants: studies on electropolished implants with different oxide thicknesses and morphology. Biomaterials, Vol. 15(13), pp. 1062–1074. https://doi.org/10.1016/0142-9612(94)90092-2
  5. Fast, J. D. (1971). Internal Friction of Metals. In: Interaction of Metals and Gases. Philips Technical Library. Palgrave, London, UK. https://doi.org/10.1007/978-1-349-00500-0_3
  6. Dorofeyev, V., Myronenko, I., Pushkar, N. (2022). The effect of technological damage on the properties and reliability of construction materials and structures. Applied Mechanics and Materials, Vol. 908, pp 149–156. https://doi.org/10.4028/p-lm1g4w
  7. Holofieieva, M., Tonkonogyi, V., Stanovska, I., Pavlyshko, A., Klimov, S. (2023). Using fractal dimensions in modeling complex systems in engineering. In: Karabegovic, I., Kovačević, A., Mandzuka, S. (eds) New Technologies, Development and Application VI. NT 2023. Lecture Notes in Networks and Systems, Vol 687. Springer, Cham. https://doi.org/10.1007/978-3-031-31066-9_32
  8. Dorofeyev, V., Pushkar, N., Zinchenko, H. (2021). The influence of concrete structure on the destruction of reinforced concrete bended elements. Proceedings of EcoComfort 2020. Lecture Notes in Civil Engineering, Vol 100. pp. 103–111. https://doi.org/10.1007/978-3-030-57340-9_13
  9. Aliha, M. R. M., Imani, D. M., Salehi, S. M., Shojaee, M., Abedi, M. (2022). Mixture optimization of epoxy base concrete for achieving highest fracture toughness and fracture energy values using Taguchi method. Composites Communications, Vo. 32, 101150. https://doi.org/10.1016/j.coco.2022.101150
  10. Szeląg, M. (2017). The influence of cement composite composition on the geometry of their thermal cracks. Construction and Building Materials, Vol. 189, pp. 1155–1172. https://doi.org/10.1016/j.conbuildmat.2018.09.078
  11. Gyekenyesi, A. L. (2002). Testing static and dynamic stresses in metallic alloys using thermoelastic stresses analysis. Materials Evaluation, Vol. 60(3), pp. 445–451.
  12. Zhan, L., Zhuang, Y. (2016). Infrared and visible image fusion method based on three stages of discrete wavelet transform. International Journal of Hybrid Information Technology, Vol. 9(5), pp. 407–418. http://dx.doi.org/10.14257/ijhit.2016.9.5.35
  13. Zhang, H., Yin, Y., Zhang, S. (2016). An improvement ELM algorithm for the measurement of hot metal temperature in blast furnace. Neurocomputing, Vol. 174(A), pp. 232–237. https://doi.org/10.1016/j.neucom.2015.04.106
  14. Balan, S. A., Stanovskaya, T. P., Stanovsky, A. L. (2002). Design and Management in Mechanical Engineering. Astroprint, Odessa, Ukraine.
  15. Chen, Y.-M., Ting J.-M. (2002). Ultra high thermal conductivity polymer composites. Carbon, Vol. 40., pp. 359–362. https://doi.org/10.1016/S0008-6223(01)00112-9
  16. Guz, N., Dokukin, M., Kalaparthi, V., Sokolov, I. (2014). If cell mechanics can be described by elastic modulus: Study of different models and probes used in indentation experiments. Biophysical Journal, Vol. 107(3), pp. 564–575. https://doi.org/10.1016/j.bpj.2014.06.033
  17. Kainer, K. U. (2006). Metal Matrix Composites: Custom-Made Materials for Automotive and Aerospace Engineering. Wiley-VCH. http://dx.doi.org/10.1002/3527608117
  18. Da Silva, R. B., Bulska, E., Godlewska-Zylkiewicz, B., Hedrich, M., Majcen, N., Magnusson, B., Marincic, S., Papadakis, I., Patriarca, M., Vassileva, E., Taylor, E. (2012). Analytical Measurement: Measurement Uncertainty and Statistics, European Union. https://doi.org/10.2787/5825
  19. Kobilskaya, E., Lyashenko, V., Hryhorova, T. (2020). Integral conditions in the inverse heat conduction problems. Mathematical Modeling and Computing, Vol. 7(2), pp. 219–227. https://doi.org/10.23939/mmc2020.02.219
  20. Yurkov, R. S., Knysh, L. I. (2021). Verification of a mathematical model for the solution of the Stefan problem using the mushy layer method. Technical Mechanics, Vol. 3, pp. 119–125. https://10.15407/itm2021.03.119

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