Bibliographic record
Abstract
The use of fibre-reinforced polymers for repair and retrofit is growing at an unprecedented rate. This technique has been used for strengthening and rehabilitation of columns, beams, masonry, joints, etc. and has also found significant suitability for seismic applications. All research to date has focused, however, on wraps and jackets with continuous, unidirectional fibres. Within the auspices of Network of Centers of Excellence on Intelligent Sensing for Innovative Structures (ISIS) program, an entirely new method of fibre reinforced polymer coating is being developed. In this method, the composite with short, randomly distributed fibres is sprayed on the surface of concrete to be repaired. Composite gets pneumatically compacted on the application surface and develops a strong bond with concrete during the hardening process. In this paper, the effectiveness of the spray technique is compared with wraps carrying continuous fibres when applied to concrete cylinders under compression. To assess size effects, a companion test series involving larger cylinders was carried out. It was found that sprayed composites with randomly distributed short fibres performed equally well as or even better than wraps with continuous fibres. Within the continuous fibre wraps, those with a 0-90° fibre orientation are far more effective than those with a ±45° orientation.Key words: concrete, repair, glass fibre, polymer matrix, spray, wraps, deformability, size effects.
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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) | 0.003 | 0.001 |
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".