MétaCan
Menu
Back to cohort
Record W2546667466 · doi:10.5267/j.esm.2016.10.001

Large plasticity induced crack initiation from U-notches in thin aluminum sheets under mixed mode loadin

2016· article· en· W2546667466 on OpenAlexvenueno aff
A.R. Torabi, Bahram Hosseini

Bibliographic record

VenueEngineering Solid Mechanics · 2016
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials sciencePlasticityMode (computer interface)AluminiumComposite materialMetallurgyStructural engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Ductile failure is investigated experimentally and theoretically in U-notched Al 7075-T6 thin sheets under mixed mode I/II loading. First, several U-notched rectangular sheets are subjected to mixed mode I/II failure tests and the load-carrying capacity of the sheets are experimentally recorded. Then, the Equivalent Material Concept (EMC) is employed in conjunction with the U-notch maximum tangential stress (UMTS) and U-notch mean stress (UMS) criteria to theoretically estimate the load-carrying capacity of the U-notched Al 7075-T6 sheets. It is shown that the experimental failure loads are well predicted by means of both the UMTS-EMC and UMS-EMC criteria. Moreover, the experimental observations and the elastic-plastic finite element analyses indicate that the U-notched aluminum sheets fail by the large-scale yielding (LSY) regime.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.245
Teacher spread0.227 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEngineering Solid MechanicsSame topicMetal Forming Simulation TechniquesFrench-language works237,207