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Record W2140031525 · doi:10.1177/1475921712469994

Acoustic emission monitoring of interlaminar delamination onset in carbon fibre composites

2013· article· en· W2140031525 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStructural Health Monitoring · 2013
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversité de MonctonUniversité de Sherbrooke
Fundersnot available
KeywordsAcoustic emissionMaterials scienceDelamination (geology)Composite materialFracture toughnessFracture mechanicsFracture (geology)Strain energy release rateEnvelope (radar)

Abstract

fetched live from OpenAlex

This article presents the development of an experimental methodology based on acoustic emission wave detection for determining delamination onset and propagation in carbon fibre composite materials under quasi-static and fatigue loading. Delamination was investigated in quasi-static interlaminar fracture testing over a wide range of mixed-mode ratios ( G II / G T = 0, 0.3, 0.5 and 1) for unidirectional and woven samples. An acoustic emission wave detection method was developed to detect delamination onset, and the corresponding fracture toughness was computed. Interlaminar fracture toughness was also calculated by beam theory and from finite element analysis with the virtual crack closure technique. The mechanical testing results, acoustic emission monitoring and numerical model’s interlaminar fracture toughness were used to define delamination initiation criteria by drawing two-dimensional envelopes corresponding to G C = f( G II / G T ). The acoustic emission wave detection method showed damage accumulation before observable crack propagation, and its failure envelope corresponded to lower fracture energies than the standard test and modelling methods. Mode I fatigue testing with acoustic emission monitoring was performed on the woven samples for different energy release rate ratios ( G IMAX / G IC = 0.3–0.8). A first series of samples were tested to construct an onset delamination fatigue curve Δ G = f( N). A second series of samples were used to study the cumulative acoustic emission energy distribution during delamination growth. An unsupervised pattern recognition methodology is presented for crack opening and closing testing, in order to discriminate between fatigue signal noise and acoustic emission signals emitted from crack initiation and crack growth. Correlations were observed between the acoustic emission energy distribution, the load range, the delamination length and the crack growth rate.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.952

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 head0.015
GPT teacher head0.286
Teacher spread0.270 · 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