Residual Tensile Properties of GFRP Reinforcing Bars after Loading in Severe Environments
Bibliographic record
Abstract
The long-term behavior of glass fiber-reinforced polymer (GFRP) reinforcing bars is one of the most critical issues for the acceptance of these materials as reinforcement for concrete structures. There is a high demand for experimental studies to investigate the stability of the tensile strength, ultimate elongation, and elasticity modulus. GFRP reinforcing bars inherently have a low elasticity modulus, which must not significantly decrease over time under loading or the serviceability behavior of the concrete element containing them will be jeopardized. This paper evaluates the residual tensile properties of three sizes of sand-coated GFRP reinforcing bars in alkaline and water environments combined with sustained loading and elevated temperature. Bar diameters of 15.9 (No. 5), 12.7 (No. 4), and 9.5mm (No. 3) were loaded for different durations, then tested in axial tension for residual tensile properties. The test periods varied from 1to4months under elevated temperature to hasten degradation and simulate extended service periods. The reduction in tensile strength was found to be 7–13% of the guaranteed strength for the three bar sizes under elevated temperature, which is at least 26% higher than the specified design strength as recommended by ACI 440.1R-03. More importantly, no significant change in the elastic modulus was observed.
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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".