Skip to main content
SpringerLink
Log in

Estimation of the Dynamics of Changing the Properties of Materials Using Neural Network Modeling

  • METHODS OF STUDYING THE STRUCTURE AND PROPERTIES OF MATERIALS. PROCESS MODELING
  • Published:
Russian Metallurgy (Metally) Aims and scope

Abstract—

The algorithms developed to describe the behavior of polymer composite materials under various loading conditions using simulation and neural network modeling are described. The main stages of these processes are described, and their advantages and disadvantages are summarized. The major input and output parameters, which should be reasonably applied for development of models intended for estimating the life of polymer composite materials, are listed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.

Similar content being viewed by others

REFERENCES

  1. A. L. Galinovskii et al., Technologies of Production and Diagnostics of Aircraft Composite Structures (TNT, Stary Oskol, 2019).

    Google Scholar 

  2. A. I. Rudskoi, A. A. Popovich, and A. V. Grigor’ev, Composite Materials and Coatings (St. Petersburg, 2017).

    Google Scholar 

  3. V. A. Zorin and V. S. Bocharov, Reliability of Machines (OrelGTU, Orel, 2003).

  4. A. P. Petrova and G. V. Malysheva, Adhesives, Binders, and Prepregs, Ed. by E. N. Kablov (VIAM, Moscow, 2017).

    Google Scholar 

  5. R. A. Turusov, Adhesive Mechanics. Monograph (NIU MGSU, Moscow, 2016).

    Google Scholar 

  6. A. S. Freidin and R. A. Turusov, Properties and Development of Adhesive Junctions (Khimiya, Moscow, 1990).

    Google Scholar 

  7. V. A. Zorin, N. I. Baurova, V. I. Balovnev, V. V. Grib, and E. A. Kosenko, “Assessing the state of mechanical systems of different complexity,” Rus. Eng. Res. 39 (8), 683–685 (2019).

    Article  Google Scholar 

  8. V. A. Zorin, N. I. Baurova, V. I. Balovnev, V. V. Grib, and E. A. Kosenko, “Informational model of state change in a mechanical system,” Rus. Eng. Res. 39 (8), 680–682 (2019).

    Article  Google Scholar 

  9. A. Yu. Sergeev, R. A Turusov, and N. I. Baurova, “Strength of the joint of an anisotropic composite and a cylindrical element of the exhaust system of road vehicles,” Mech. Comp. Mater. 52 (1), 89–98 (2016).

    Article  CAS  Google Scholar 

  10. A. I. Rudskoi and N. I. Baurova, “Technological heredity during the production and operation of structural materials,” Russ. Metall. (Metally), No. 13, 1378–1383 (2019).

  11. N. I. Baurova and A. Yu. Konoplin, “Technological heredity and models of its visualization,” Tekhnol. Met., No. 1, 38–42 (2020).

  12. V. A. Nelyub, A. S. Borodulin, L. P. Kobets, and G. V. Malysheva, “Viscous hysteresis in filled siloxane binders,” Polym. Sci.: Series D, No. 10(1), 19–22 (2017).

  13. G. V. Malysheva and T. A. Guzeva, “Accuracy of manufacture of pars from polymer composite materials,” Tekhnol. Met., No. 11, 3–9 (2020).

Download references

Funding

This work was supported by project no. FSFM-2020-0011 (2019-1342).

Author information

Authors and Affiliations

  1. Moscow Automobile and Road Construction State Technical University (MADI), 125319, Moscow, Russia

    N. I. Baurova & A. Yu. Konoplin

Authors
  1. N. I. Baurova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Yu. Konoplin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. I. Baurova.

Additional information

Translated by I. Moshkin

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baurova, N.I., Konoplin, A.Y. Estimation of the Dynamics of Changing the Properties of Materials Using Neural Network Modeling. Russ. Metall. 2021, 1713–1718 (2021). https://doi.org/10.1134/S0036029521130036

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0036029521130036

Keywords:

Search

Navigation