Nizhny Novgorod State Technical University named after R. E. Alekseev, Nizhny Novgorod, Russia:

D. A. Ryabov, Post-graduate Student, Assistant, Researcher of the Dept. of Materials Science, Materials Technology and Heat Treatment of Metals, e-mail: ryabovdm1996@gmail.com
M. S. Anosov, Cand. Eng., Associate Prof., Dept. of Technology and Equipment of Mechanical Engineering, e-mail: anosov-maksim@list.ru
A. A. Khlybov, Dr. Eng., Prof., Head of the Dept. of Materials Science, Materials Technology and Heat Treatment of Metals, e-mail: hlybov_52@mail.ru

The paper considers the issues of structural degradation under alternating loading of 09Mn2Si steel samples obtained using wire arc additive manufacturing (WAAM). At the moment, an urgent task is to study the processes of accumulation of degradation of metal materials obtained by the WAAM method, as well as the search and testing by non-destructive testing of the damaged state of such materials. In the course of the work, an assessment of the mechanical properties of samples made of steel 09Mn2Si cut from the workpiece in the direction along and across the deposition of layers is given. The curves of low-cycle fatigue for longitudinally and transversely cut samples are studied. It was found that the mechanical properties (including fatigue) of samples cut along the direction of surfacing are up to 10 % higher than those of samples cut across. The structural changes taking place in the studied material during cyclic loading are shown. To assess structural changes, a method of digital analysis of microstructure images (determination of the fractal dimension index) obtained with different operating time was used. The change in the acoustic and magnetic characteristics of the printed material from the number of cycles under alternating loading and the relationship between operating time and coercive force are established. The results obtained in the work can be used to monitor the current state of printed parts and structures made of 09Mn2Si steel subjected to cyclic loading.
The work was supported by the Russian Science Foundation grant No. 19-19-00332-P "Development of science-based approaches and hardware and software tools for monitoring the damage of structural materials based on artificial intelligence approaches to ensure the safe operation of technical facilities in the Arctic conditions".

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