Structural failure at low temperatures and stability diagnostics


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The influence of impurities on the cold brittleness of materials is studied. A neural network is trained to model fatigue and brittle failure of samples. The neural network generates numerical sequences that evolve analogously to the fractal characteristics of acoustic emission studied in fatigue tests with various loads.

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Yu. Kabaldin

Alekseev Nizhegorodsk State Technical University

编辑信件的主要联系方式.
Email: uru.40@mail.ru
俄罗斯联邦, Nizhny Novgorod, 603905

I. Laptev

Alekseev Nizhegorodsk State Technical University

Email: uru.40@mail.ru
俄罗斯联邦, Nizhny Novgorod, 603905

D. Shatagina

Alekseev Nizhegorodsk State Technical University

Email: uru.40@mail.ru
俄罗斯联邦, Nizhny Novgorod, 603905

M. Anosova

Alekseev Nizhegorodsk State Technical University

Email: uru.40@mail.ru
俄罗斯联邦, Nizhny Novgorod, 603905

V. Zotova

Alekseev Nizhegorodsk State Technical University

Email: uru.40@mail.ru
俄罗斯联邦, Nizhny Novgorod, 603905

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