Flexural behaviour of the segmental precast concrete decks post-tensioned by GFRP rods
Bibliographic record
Abstract
This paper introduces an innovative post-tensioned segmental concrete deck system internally reinforced and tied with GFRP reinforcements for application in pontoon decks and other deck structures in aggressive marine environments. Utilisation of the GFRP reinforcements in floating concrete structures is essential because of their non-corrosive characteristics. Six large-scale segmental decks following the specifications of Queensland maritime infrastructure were designed, manufactured, and tested to assess the reliability of the new construction system under static flexural loading in the flatwise and edgewise orientations. One segmental deck served as a reference with hand-tight post-tensioning, while the remaining specimens were connected by the GFRP rods with varying levels of post-tensioning. All decks were tested up to failure, allowing for an investigation of their flexural strength, load-strain behaviour, joint opening, and failure mechanism. The results showed that post-tensioning the GFRP rods improves the flexural performance of the segmental decks. The higher the level of post-tensioning, the higher the contact area between the segments at the joint is achieved. A numerical model was developed to understand the detailed mechanism of both flatwise and edgewise specimens. A strain reduction coefficient in the segmental concrete deck under flexure is introduced accounting for the joint presence to reliably calculate the stress in the post-tensioned internal GFRP rod when the concrete in the joint crushes. The system investigated can increase maritime and recreational infrastructure's construction efficiency and provide creative solutions in the GFRP-reinforced concrete structures in the building and construction industry.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".