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Optimization of Johnson-Cook Constitutive Model Parameters Using the Nesterov Gradient-Descent Method.

作者信息

Zelepugin Sergey A, Cherepanov Roman O, Pakhnutova Nadezhda V

机构信息

Tomsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences, 634055 Tomsk, Russia.

出版信息

Materials (Basel). 2023 Aug 3;16(15):5452. doi: 10.3390/ma16155452.

DOI:10.3390/ma16155452
PMID:37570157
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10419794/
Abstract

Numerical simulation of impact and shock-wave interactions of deformable solids is an urgent problem. The key to the adequacy and accuracy of simulation is the material model that links the yield strength with accumulated plastic strain, strain rate, and temperature. A material model often used in engineering applications is the empirical Johnson-Cook (JC) model. However, an increase in the impact velocity complicates the choice of the model constants to reach agreement between numerical and experimental data. This paper presents a method for the selection of the JC model constants using an optimization algorithm based on the Nesterov gradient-descent method. A solution quality function is proposed to estimate the deviation of calculations from experimental data and to determine the optimum JC model parameters. Numerical calculations of the Taylor rod-on-anvil impact test were performed for cylindrical copper specimens. The numerical simulation performed with the optimized JC model parameters was in good agreement with the experimental data received by the authors of this paper and with the literature data. The accuracy of simulation depends on the experimental data used. For all considered experiments, the calculation accuracy (solution quality) increased by 10%. This method, developed for selecting optimized material model constants, may be useful for other models, regardless of the numerical code used for high-velocity impact simulations.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/a3b378e4e7b4/materials-16-05452-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/79bfa447d4b4/materials-16-05452-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/98f0c1e530de/materials-16-05452-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/e3ae214ccd59/materials-16-05452-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/58fecc6c70b5/materials-16-05452-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/a3b378e4e7b4/materials-16-05452-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/79bfa447d4b4/materials-16-05452-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/98f0c1e530de/materials-16-05452-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/e3ae214ccd59/materials-16-05452-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/58fecc6c70b5/materials-16-05452-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe4/10419794/a3b378e4e7b4/materials-16-05452-g005.jpg

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