Durability of GFRP composite rods : Results from preliminary field tests don't match data from accelerated lab tests
Bibliographic record
Abstract
A primary durability concern in concrete structures with high exposure to chlorides is rapid corrosion rates of reinforcing steel. Chemically-inert materials such as fiber-reinforced polymers have been suggested as reinforcing alternatives that eliminate corrosion. Glass-fiber-reinforced polymer (GFRP) is the most economical of these, but has been reported to be very vulnerable to concrete's highly alkaline environment. Studies conducted in idealized simulated environments found GFRP should not be in contact with concrete. Simulated conditions included unlimited hydroxyl ion supply, not present in actual conditions, and full saturation, rare in actual conditions. Intelligent Sensing for Innovative Structures Canada (ISIS Canada) conducted a major 2004 field study on GFRP rods in a variety of bridges. The results contradicted those gained in laboratory environments. It found no degradation of GFRP in structures exposed to natural environmental conditions for 5-8 years. Results were the basis for a new version of the Canadian Highway Bridge Design Code, allowing use of GFRP both as primary reinforcement and prestressing tendons in concrete components under certain stress levels.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 0.002 |
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".