Evidence map›Paper›PMID 37570157›Full record

ArticleMaterials (Basel, Switzerland)2023

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

Sergey A Zelepugin, Roman O Cherepanov, Nadezhda V Pakhnutova

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sergey A ZelepuginTomsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences, 634055 Tomsk, Russia.ORCID 0000-0002-1209-4580
Roman O CherepanovTomsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences, 634055 Tomsk, Russia.ORCID 0000-0003-1960-8991
Nadezhda V PakhnutovaTomsk Scientific Center of the Siberian Branch of the Russian Academy of Sciences, 634055 Tomsk, Russia.

Funding

Ministry of Science and Higher Education of the Russian Federation 121031800149-2
6 · The paper itself

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.

Indexed as

finite element simulationhigh strain-ratesJohnson–Cook (JC) constitutive modelNesterov gradient-descent methodshock wavesTaylor impact test

Identifiers

PMID37570157
PMCPMC10419794

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.