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Propriedades mecânicas de tração e fadiga de chapa fina de um aço livre de intersticiais

2016· dissertation· pt· W2800922343 on OpenAlexaff
Marcelo Milan

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsFuture Earth
Fundersnot available
KeywordsHumanitiesMaterials sciencePhilosophyPhysics

Abstract

fetched live from OpenAlex

In the present work, the monotonic and low cyc1efatigue properties of thin sheet of interstitial free steel containing titanium additions, used in the automotive industry, were investigated.Fatigue tests were conducted under deformation control (R;=-1) using a grip alignrnent fixture.The material exhibits different fatigue behavior for the transverse and longitudinal directions (in relation to the rolling direction).A comparison between the monotonic stress-strain curve and the cyc1ic stress-strain curve in the transverse direction showed that the material exhibits cyc1ichardening in alI strain amplitudes tested.The strain-life relationship obtained for transverse direction is given by 8.Et/2= O, O186(2Nfro,262 + 0,235(2Nf)-O,476 with transition point in 2Nt=1,4x105 reverses; buck1ing of longitudinal specimens made impossible to obtain such relationship.Several prediction methods of fatigue properties from monotonic properties were compared to the experimental results.The Four Point Correlation and the Modified Universal Slopes Methods showed a good correlation for the low cyc1eregion.Fractographic analysis through Scanning Eletronic Microscopy showed the presence of Stage 11striations, giving support to the high ductility of the material.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

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 communication0.0010.000
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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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