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4_2025_sen_9

Title of the article INTELLIGENT MODELS OF WEAR-FATIGUE DAMAGE AND FRACTURE MECHANICS
Authors

SHERBAKOV Sergei S., D. Sc. in Phys. and Math., Prof., Deputy Chairman of the Presidium, National Academy of Sciences of Belarus, Minsk, Republic of Belarus; Chief Researcher, Joint Institute of Mechanical Engineering of the NAS of Belarus, Minsk, Republic of Belarus; This email address is being protected from spambots. You need JavaScript enabled to view it.">This email address is being protected from spambots. You need JavaScript enabled to view it.
In the section TRIBO-FATIGUE SYSTEMS MECHANICS
Year 2025
Issue 4(73)
Pages 66–75
Type of article RAR
Index UDK 531; 004.8
DOI https://doi.org/10.46864/1995-0470-2025-4-73-66-75
Abstract Artificial intelligence technologies are considered in comparison with mathematical modeling using the examples of a number of critical purpose technical systems studied in tribo-fatigue. An applied definition of artificial intelligence as a technical automated system rather than a set of specific technologies is proposed. Tribo-fatigue methodology is presented for the consistent formulation and solution of interaction problems of a system with many bodies with previously unknown contact surfaces, determination and prediction of their three-dimensional stress-strain state, volumetric damage state and multi-criteria limiting states taking into account its simultaneous complex thermal-force loading by contact and non-contact forces. This made it possible to create multi-element digital twins of a number of technical systems of critical purpose, used to optimize these systems for damage and support management decisions. Unified approach is proposed to application of artificial neural networks and mathematical modeling in intelligent models of tribo-fatigue and mechanothermodynamic systems. Beneficial direct effect of artificial neural networks on approximation of mathematical modeling results and opposite effect of good quality data produced by mathematical modeling on artificial neural networks are shown.
Keywords tribo-fatigue, artificial intelligence, mathematical modeling, artificial neural networks, mechanothermodynamics
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