Evidence map›Paper›PMID 36770090›Full record

ArticleMaterials (Basel, Switzerland)2023

Prediction of True Stress at Hot Deformation of High Manganese Steel by Artificial Neural Network Modeling.

Alexander Yu Churyumov, Alena A Kazakova

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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

2 authors.

Alexander Yu ChuryumovDepartment of Physical Metallurgy of Non-Ferrous Metals, National University of Science and Technology "MISiS", Leninskiy Prospekt 4, 119049 Moscow, Russia.ORCID 0000-0003-0933-056X
Alena A KazakovaDepartment of Physical Metallurgy of Non-Ferrous Metals, National University of Science and Technology "MISiS", Leninskiy Prospekt 4, 119049 Moscow, Russia.

Funding

Russian Science Foundation 18-79-10153-PStrategic Academic Leadership Program "Priority 2030" K2-2022-001
6 · The paper itself

Abstract

The development of new lightweight materials is required for the automotive industry to reduce the impact of carbon dioxide emissions on the environment. The lightweight, high-manganese steels are the prospective alloys for this purpose. Hot deformation is one of the stages of the production of steel. Hot deformation behavior is mainly determined by chemical composition and thermomechanical parameters. In the paper, an artificial neural network (ANN) model with high accuracy was constructed to describe the high Mn steel deformation behavior in dependence on the concentration of the alloying elements (C, Mn, Si, and Al), the deformation temperature, the strain rate, and the strain. The approval compression tests of the Fe-28Mn-8Al-1C were made at temperatures of 900-1150 °C and strain rates of 0.1-10 s

Indexed as

artificial neural networkconstitutive modelhigh Mn steelhot deformationthermomechanical simulator Gleeble

Identifiers

PMID36770090
PMCPMC9920467

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.