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Record W4308865021 · doi:10.5267/j.esm.2022.9.002

Stress state of workpieces during upsetting with additional shear

2022· article· en· W4308865021 on OpenAlexvenueno aff
Zhassulan Ashkeyev, Maxat Abishkenov, Kayrosh Nogaev

Bibliographic record

VenueEngineering Solid Mechanics · 2022
Typearticle
Languageen
FieldEngineering
TopicEngineering Technology and Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceShear (geology)SchematicUltimate tensile strengthSlip (aerodynamics)Finite element methodShear stressStress (linguistics)Composite materialMetallurgyAlloyDeformation (meteorology)Structural engineeringEngineering

Abstract

fetched live from OpenAlex

The article presents an analysis of the stress state of workpieces during upsetting of workpieces with an additional shear. For the analysis, the slip line method and the finite element method were used. A schematic diagram of upsetting in dies with “floating” elements, contributing to the implementation of additional shear, reduction of barreling, inhomogenous deformation and contour tensile stresses, is presented. The analysis of the research results showed that during upsetting of workpieces with additional shift forces, tensile stresses on the side surface of the workpieces decrease, which excludes the appearance of cracks on the side surface of the samples, especially when processing low-plastic alloy steels and alloys, and also reduces the barreling of the side surface.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.198
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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