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Record W4409721868 · doi:10.1007/s11340-025-01184-z

Improving Reversed Three-Point Bending Tests for Characterising the Fatigue Life of Polymers

2025· article· en· W4409721868 on OpenAlexfundno aff
Simon Baril-Gosselin

Bibliographic record

VenueExperimental Mechanics · 2025
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsSolid mechanicsMaterials sciencePolymerBendingComposite materialStructural engineeringPoint (geometry)EngineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract Background Cyclic loading is a leading cause of material failure and accurate testing methods are required to predict the life of components. Objective This work investigated the challenges of performing reversed three-point bending experiments for characterising the fatigue life of polymers and composites, and sought to develop guidelines for improving the testing method. Methods Testing was performed with polypropylene (PP) and glass-fibre reinforced PP on a test fixture that featured double-sided supports. Monotonic and fully reversed (i.e. stress ratio R = - 1) cyclic bending experiments were conducted to characterise the effects that the test conditions, including the type of supports and level of contact between the specimens and anvils, have on the measurements. Results Stresses generated during reversed bending are highly dependent on the type of fixture configuration used. Most configurations that were tested led to mechanical interlocking that altered the bending moments and generated membrane stresses. In this work, the purest form of reversed bending was achieved using double-sided pivoting supports, and a 0.35 mm gap between specimens and anvils to allow sliding in the supports. Conclusions This configuration provided the most similar stress state to that obtained from the standardised simply-supported beam experiments that are used for characterising the quasi-static flexural properties of materials, and was ultimately the configuration that provided the most reliable fatigue data.

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 score0.410
Threshold uncertainty score0.779

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 head0.028
GPT teacher head0.286
Teacher spread0.259 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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