Improving Reversed Three-Point Bending Tests for Characterising the Fatigue Life of Polymers
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".