Tension stiffening and cracking of concrete reinforced with glass fiber reinforced polymer (GFRP) bars
Bibliographic record
Abstract
Tension stiffening and cracking of axial tension members is evaluated for concrete reinforced with steel (reinforcing ratio ρ = 2.0%) and glass fiber reinforced polymer (GFRP) bars (1.3%, 2.0%, and 2.9%), with shrinkage included in the analysis of the member response. Results show that because of a lower bar stiffness the GFRP-reinforced concrete exhibits greater tension stiffening than steel-reinforced concrete for any given value of axial member strain. Transverse cracking in the GFRP-reinforced concrete does not stabilize until much higher values of axial strain are reached, and longitudinal splitting cracks are also evident before cracking has stabilized. Crack widths in concrete reinforced with GFRP bars are larger because of their lower bar stiffness in combination with an increased crack spacing during the crack development stage. Tension stiffening of cracked reinforced concrete is taken into account using an average stress-strain response with a descending branch to model the concrete in tension. A tension stiffening factor is used to characterize this tensile property with an empirical relationship related to the reinforcing bar stiffness and independent of both concrete strength and reinforcing ratio. Results are also compared with the predicted member response based on the 1978 Comité Euro-International du Béton (CEB) CEB-FIP model code approach and American Concrete Institute (ACI) method of using an effective cracked section property for the transformed concrete area. This comparison shows that both methods are valid only for a limited range of reinforcing ratios.Key words: cracking, crack spacing, crack width, GFRP, reinforced concrete, tension stiffening.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".