Experimental Investigation of the Behaviour of Short-Span FRP-Reinforced Glulam Beams with Hoops and Tension Anchoring
Bibliographic record
Abstract
Past research has shown that for short-span glulam beams reinforced with a simple tension GFRP fabric can lead to undesirable failure modes at the reinforcement termination point. An experimental programme aimed at investigating alternative reinforcement schemes comprising hoops and tension anchoring as an alternative to fan-type anchorage and full-length confinement was undertaken. Sixteen GFRP-reinforced glulam beams were tested to failure under four-point bending. Overall, the hoops and tension anchoring prevented premature debonding and stress concentration failures observed in beams reinforced with simple tension reinforcement. Improvements in the stiffness and strength were generally observed for all configurations with the average failure strain being on average 1.16 times larger than the unreinforced specimens. While hoops prevented undesirable failure modes, it had limited improvements when using bidirectional fabrics for the hoops. Conversely, the configurations with tension anchoring using bidirectional fabrics only resulted in improved performance with some level of post-peak resistance compared to the unreinforced specimens and those reinforced with simple tension reinforcement. For short-span beams, or any FRP-reinforced glulam beams where flexure is not the dominant failure mode, more robust modelling techniques are required to properly capture the distribution of the reinforcement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".