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Cyclic Damage Evolution in a PMC Laminate

2007· article· en· W1977761909 on OpenAlexaff
A. Plumtree, Mírian de Lourdes Noronha Motta Melo

Bibliographic record

VenueKey engineering materials · 2007
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceComposite materialModulusStress (linguistics)Transverse planeAntisymmetric relationStructural engineeringEpoxyStress concentrationDamage mechanicsFracture mechanicsFinite element methodMathematics

Abstract

fetched live from OpenAlex

Using damage mechanics, cyclic damage evolution has been described and evaluated in a non-crimped glass epoxy fabric composite. A fundamental fatigue study has been carried out by progressively monitoring the fatigue damage modulus and crack density throughout the life of an [0,+45,90,-45]2 (antisymmetric) laminate cycled at a stress ratio R (minimum stress/maximum stress) of 0.1. Development of damage can be separated into two main stages. Initially, damage increases very quickly during the first 10% of life (Stage I). Afterwhich, it increases more slowly at a relatively constant rate to failure (Stage II). The changes in the fatigue modulus and crack density both show the same behaviour. A large amount of damage in the form of transverse matrix cracks develops during the first cycle. These then remain constant throughout life. By contrast, the number of shear matrix cracks increase continually. The crack density is cycle, not stress dependent. This behaviour is reflected by changes in the fatigue modulus. Using damage mechanics, a representative equation has been applied to express the progressive evolution of damage. The significance of which is that the amount of fatigue damage at the end of Stage I for any stress level can be used to predict fatigue life and the stress-life diagram for the laminate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.133
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 teacher head, 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

Citations1
Published2007
Admission routes1
Has abstractyes

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