Flexural strength of post-tensioned concrete-filled fiber-reinforced polymer rectangular tube beams
Bibliographic record
Abstract
This study extends an extensive research program carried out at the University of Sherbrooke to design and assess the potential use of rectangular, concrete-filled fiber-reinforced-polymer tube (CFFT) beams post-tensioned with steel tendons in bridge applications. This paper describes research to enhance the flexural performance of post-tensioned CFFT beams. Five rectangular post-tensioned CFFT beams were tested up to failure, and the effects of attaching a thin carbon-fiber-reinforced polymer (CFRP) laminate embedded in tension flange and its total reinforcement ratio as well as tube structure fiber laminate were investigated. Last, a simplified design approach is proposed based on strain combinability and force equilibrium to estimate the flexural moment capacity of the tested beams. The specimens with two inclined fiber patterns in the hoop direction or added CFRP laminate strips embedded in the bottom flange of the tubes exhibited substantially greater flexural strength, absorbed energy, and serviceability performance than the control specimens. The ductility index and energy ratio ranged from 8.3 to 10.6 and from 82% to 87%, respectively, which indicates ductile behavior. Also, adding CFRP laminate strips embedded in the bottom flange of the tubes enhanced the flexural strength by 17% on average compared with post-tensioned CFFT without CFRP laminate. The specimen with the CFRP laminates in the bottom flange of the tube achieved flexural strength and energy absorption that was comparable to the flexural strength and energy absorption of the specimen with two layers of inclined fiber patterns. The findings suggest that the design can be optimized to achieve more efficient post-tensioned CFFT structural members. The proposed design approach successfully predicts the flexural strength of the tested beams with an average of 1.05 ± 0.05 for the partially confined concrete model and an average of 1.11 ± 0.07 for the unconfined concrete model.
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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) | 0.002 | 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".