Flexural behavior of beams strengthened with <scp>GFRP</scp> bars and high‐performance fiber‐reinforced concrete
Bibliographic record
Abstract
Abstract The flexural behavior of beams strengthened with GFRP bars and high‐performance fiber‐reinforced concrete (HPFRC) was investigated in this paper. The four‐point flexural response of one reference beam and four beams strengthened with high‐performance fiber‐reinforced concrete was investigated by experimental research and theoretical calculation. The experimental and theoretical data (strain, load, etc.) are discussed. Parameters varied included the strengthening scheme (bottom‐side strengthening and three‐side strengthening) and the type of high‐performance fiber‐reinforced concrete (engineered cementitious composite [ECC] and ultra‐high‐performance concrete [UHPC]). The results showed that the cracking load and ultimate load of beams strengthened with UPFRC material were 31.3%–170% and 9.6%–20.7% higher, respectively, relative to the reference beam. Beams with three‐side strengthening (without interfacial debonding) had higher ultimate load, smaller crack width, and better durability relative to beams with bottom‐side strengthening. The UHPC layer was more effective in increasing the ultimate bearing capacity, and ECC strengthening layer was more effective in inhibiting cracking development of beams. Based on the experimental results, a model was proposed to predict the ultimate bearing capacity of beams strengthened with high‐performance fiber‐reinforced concrete, which could provide good agreement between the experimental and predicted results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".