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Compression-compression fatigue of quasi-isotropic laminates: Failure mechanisms and link between dissipative behavior and fatigue life

2024· article· en· W4405495102 on OpenAlexaff
Otávio Zimmermann de Almeida, Nicolas Carrère, M. Le Saux, V. Le Saux, G. Moreau, Yannick Pannier, Sylvie Castagnet, Y. Marco

Bibliographic record

VenueInternational Journal of Fatigue · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsSafran Electronics (Canada)
FundersAssociation Nationale de la Recherche et de la TechnologieAgence Nationale de la RechercheNaval Group
KeywordsDissipative systemMaterials scienceCompression (physics)IsotropyStructural engineeringFatigue testingGoodman relationComposite materialEngineeringStress concentrationFracture mechanicsPhysics

Abstract

fetched live from OpenAlex

• The failure mechanisms of a quasi-isotropic laminate under compression-compression cyclic loading are determined. • Linking cyclic dissipation from self-heating measurements, to dissipation in each ply and failure of the laminate. • Rapid determination of the fatigue limit of the laminate from the self-heating curve and a viscoelastic behavior law. • The predictions are consistent with fatigue test results up to 1x108 cycles. Few studies have investigated the fatigue of composite laminates under cyclic compression loading. Moreover, the self-heating approach to rapidly predict fatigue life has rarely been applied to this type of material. The objective of this work is to study the fatigue of a quasi-isotropic laminate under compression-compression loadings and to assess the possibility of rapidly determining an endurance limit from a self-heating test. Compression-compression fatigue and self-heating tests were carried out on a carbon/epoxy quasi-isotropic laminate with a stress ratio of 10. Fatigue tests were conducted for lifetimes up to 10 8 cycles. The damage scenario is investigated by interrupting fatigue tests and conducting subsequent observations of the samples using scanning electron microscopy and X-ray micro-computed tomography. A methodology for analyzing self-heating tests is applied, which allows the determination of the mean volumetric intrinsic cyclic dissipation of the laminate from surface thermal measurements. A method using a viscoelastic constitutive law is proposed to estimate the endurance limit from the self-heating curve.

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 score0.247
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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