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Record W4200477718 · doi:10.5267/j.esm.2021.12.001

A comparative analysis of the stress-strain state of disc specimens in assessing the structural strength of materials

2021· article· en· W4200477718 on OpenAlexvenueno aff
Л. Б. Цвик, Е. V. Zenkov

Bibliographic record

VenueEngineering Solid Mechanics · 2021
Typearticle
Languageen
FieldEngineering
TopicEngineering Technology and Methodologies
Canadian institutionsnot available
Fundersnot available
KeywordsSSS*Structural engineeringPrincipal stressStress (linguistics)Materials scienceStress–strain curveFinite element methodComposite materialComputer scienceEngineeringShear stress

Abstract

fetched live from OpenAlex

A study of the stress-strain state (SSS) of disc specimens has been conducted when testing specimens with stress concentrators (grooves). The research has shown that the truncation of circular discs along two symmetrical chords makes it possible to change the type (the ratio of principal stresses) of SSS that occurs at the destruction site. Therefore, these specimens can be used to assess the structural strength of materials on standard single-drive testing machines, taking into account the real type of SSS that occurs in the bearing elements of machines. The results of numerical SSS modeling have been used to build the dependences of the SSS type and level on geometric parameters of specimens. Geometrical parameters can be chosen for a certain SSS type to assess both the static and fatigue strengths of materials used in the manufacture of bearing elements.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.301
Teacher spread0.275 · 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 designBench or experimental
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

Citations3
Published2021
Admission routes1
Has abstractyes

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