PSI - Issue 59

Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2023) 000 – 000 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2023) 000 – 000

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

ScienceDirect

Procedia Structural Integrity 59 (2024) 271–278

© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of DMDP 2023 Organizers Abstract Various approaches for studying the jump-like deformation of AMg6 aluminum alloy are being compared. AMg6 alloy is characterized by instantaneous deformation increases during uniaxial stretching in the area of plasticity. It was assumed that the process of jump-like tensile deformation is caused by the cracking of dispersoids in the volume of the material. Based on that assumption, the methods that predict the initiation and magnitude of jump-like deformation depending on the proportion of destroyed inclusions were proposed. In particular, the ANSYS software complex was used to predict jump-like deformation, in which the groups of finite element models were developed to determine the main patterns of influence of structural heterogeneity parameters of the simulated environment on the stress-strain state. In addition, given the large amount of experimental data, it is important to learn how to solve such problems using machine learning (ML), particularly neural networks. It has been established that the prediction accuracy by one of the most common ML methods, that was neural networks, comprised more than 90%. © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of DMDP 2023 Organizers Keywords: AMg6 aluminum alloy; jump-like deformation; machine learning, neural networks 1. Introduction One of the main characteristics of the materials is the parameters describing the deformation diagram during uniaxial tension at a constant loading rate. Some structural alloys, particularly the AMg6 aluminum alloy, are VII International Conference “In -service Damage of Materials: Diagnostics and Prediction ” (DMDP 2023) Methods of jump-like modeling of the discontinuous yield of AMg6 aluminum alloy Oleh Yasniy a , Sergiy Fedak a , Iryna Didych a, *, Sofia Fedak a , Nadiya Kryva a Ternopil Ivan Puluj National Technical University, Ruska str. 56, Ternopil, 46001, Ukraine Abstract Various approaches for studying the jump-like deformation of AMg6 aluminum alloy are being compared. AMg6 alloy is characterized by instantaneous deformation increases during uniaxial stretching in the area of plasticity. It was assumed that the process of jump-like tensile deformation is caused by the cracking of dispersoids in the volume of the material. Based on that assumption, the methods that predict the initiation and magnitude of jump-like deformation depending on the proportion of destroyed inclusions were proposed. In particular, the ANSYS software complex was used to predict jump-like deformation, in which the groups of finite element models were developed to determine the main patterns of influence of structural heterogeneity parameters of the simulated environment on the stress-strain state. In addition, given the large amount of experimental data, it is important to learn how to solve such problems using machine learning (ML), particularly neural networks. It has been established that the prediction accuracy by one of the most common ML methods, that was neural networks, comprised more than 90%. © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of DMDP 2023 Organizers Keywords: AMg6 aluminum alloy; jump-like deformation; machine learning, neural networks 1. Introduction One of the main characteristics of the materials is the parameters describing the deformation diagram during uniaxial tension at a constant loading rate. Some structural alloys, particularly the AMg6 aluminum alloy, are VII International Conference “In -service Damage of Materials: Diagnostics and Prediction ” (DMDP 2023) Methods of jump-like modeling of the discontinuous yield of AMg6 aluminum alloy Oleh Yasniy a , Sergiy Fedak a , Iryna Didych a, *, Sofia Fedak a , Nadiya Kryva a Ternopil Ivan Puluj National Technical University, Ruska str. 56, Ternopil, 46001, Ukraine

* Corresponding author. +380972272074. E-mail address: iryna.didych1101@gmail.com * Corresponding author. +380972272074. E-mail address: iryna.didych1101@gmail.com

2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of DMDP 2023 Organizers 2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of DMDP 2023 Organizers

2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of DMDP 2023 Organizers 10.1016/j.prostr.2024.04.039

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