Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem
Molecular dynamics (MD) simulations explored the deformation behavior of copper single crystal under various axisymmetric loading paths. The obtained MD dataset was used for the development of a machine-learning-based model of elastic–plastic deformation of copper. Artificial neural networks (ANNs)...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/12/3/402 |
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| author | Alexander E. Mayer Mikhail V. Lekanov Natalya A. Grachyova Eugeniy V. Fomin |
| author_facet | Alexander E. Mayer Mikhail V. Lekanov Natalya A. Grachyova Eugeniy V. Fomin |
| author_sort | Alexander E. Mayer |
| collection | DOAJ |
| description | Molecular dynamics (MD) simulations explored the deformation behavior of copper single crystal under various axisymmetric loading paths. The obtained MD dataset was used for the development of a machine-learning-based model of elastic–plastic deformation of copper. Artificial neural networks (ANNs) approximated the elastic stress–strain relation in the form of tensor equation of state, as well as the thresholds of homogeneous nucleation of dislocations, phase transition and the beginning of spall fracture. The plastic part of the MD curves was used to calibrate the dislocation plasticity model by means of the probabilistic Bayesian algorithm. The developed constitutive model of elastic–plastic behavior can be applied to simulate the shock waves in thin copper samples under dynamic impact. |
| first_indexed | 2024-03-09T13:20:57Z |
| format | Article |
| id | doaj.art-f9e4029070b9427297deadaa592608b7 |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-09T13:20:57Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-f9e4029070b9427297deadaa592608b72023-11-30T21:30:40ZengMDPI AGMetals2075-47012022-02-0112340210.3390/met12030402Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave ProblemAlexander E. Mayer0Mikhail V. Lekanov1Natalya A. Grachyova2Eugeniy V. Fomin3Department of Physics, Chelyabinsk State University, 454001 Chelyabinsk, RussiaDepartment of Physics, Chelyabinsk State University, 454001 Chelyabinsk, RussiaDepartment of Physics, Chelyabinsk State University, 454001 Chelyabinsk, RussiaDepartment of Physics, Chelyabinsk State University, 454001 Chelyabinsk, RussiaMolecular dynamics (MD) simulations explored the deformation behavior of copper single crystal under various axisymmetric loading paths. The obtained MD dataset was used for the development of a machine-learning-based model of elastic–plastic deformation of copper. Artificial neural networks (ANNs) approximated the elastic stress–strain relation in the form of tensor equation of state, as well as the thresholds of homogeneous nucleation of dislocations, phase transition and the beginning of spall fracture. The plastic part of the MD curves was used to calibrate the dislocation plasticity model by means of the probabilistic Bayesian algorithm. The developed constitutive model of elastic–plastic behavior can be applied to simulate the shock waves in thin copper samples under dynamic impact.https://www.mdpi.com/2075-4701/12/3/402dynamic deformationshock wavecopperconstitutive equationsequation of statehomogeneous nucleation of dislocations |
| spellingShingle | Alexander E. Mayer Mikhail V. Lekanov Natalya A. Grachyova Eugeniy V. Fomin Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem Metals dynamic deformation shock wave copper constitutive equations equation of state homogeneous nucleation of dislocations |
| title | Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem |
| title_full | Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem |
| title_fullStr | Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem |
| title_full_unstemmed | Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem |
| title_short | Machine-Learning-Based Model of Elastic—Plastic Deformation of Copper for Application to Shock Wave Problem |
| title_sort | machine learning based model of elastic plastic deformation of copper for application to shock wave problem |
| topic | dynamic deformation shock wave copper constitutive equations equation of state homogeneous nucleation of dislocations |
| url | https://www.mdpi.com/2075-4701/12/3/402 |
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