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Record W2126294298 · doi:10.1177/0731684407079771

A Fatigue Damage Model for (0/90) FRP Composites based on Stiffness Degradation of 0° and 90° Composite Plies

2007· article· en· W2126294298 on OpenAlexaff
A. Varvani‐Farahani, Alireza Sahami Shirazi

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2007
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceComposite materialFibre-reinforced plasticStiffnessComposite numberComposite laminatesCrackingStress (linguistics)FiberFiber-reinforced compositeReduction (mathematics)Damage toleranceMatrix (chemical analysis)Structural engineering

Abstract

fetched live from OpenAlex

The present study develops a stiffness reduction based model to characterize fatigue damage in unidirectional 0° and 90° plies and (0°/90°) laminates of fiber-reinforced polymer (FRP) composites. The proposed damage model has been developed, based on (i) cracking mechanism and damage progress in matrix (Region I), matrix-fiber interface (Region II) and fiber (Region III) and (ii) corresponding stiffness reduction of unidirectional composite laminates as the number of cycles progresses. Fatigue damage of (0/90)°composite systems was obtained by integrating damage values and occurred in composite plies of 0 and 90° under fatigue cycles. The predicted fatigue damage results based on the proposed damage model were found to be in good agreement for both unidirectional and (0/90) FRP composites, as they were compared with experimental data for these materials, tested at various cyclic stress levels, stress ratios, and off-axis angles reported in the literature.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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

Citations57
Published2007
Admission routes1
Has abstractyes

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