Performance of Precast FRC Tunnel Lining Segments Reinforced with GFRP Bars under Quasi-Static Cyclic Flexural Loading
Bibliographic record
Abstract
Precast fiber-reinforced concrete (FRC) tunnel lining segments are designed using fundamental principles recommended in various international design provisions and guidelines. Current design provisions, however, do not apply to designing precast concrete tunnel (PCTL) segments reinforced internally with fiber-reinforced polymer (FRP) bars. Moreover, the behavior of PCTL segments reinforced internally with glass-FRP (GFRP) bars under quasi-static cyclic flexural loading is a field in which no experimental research results are available in practice. This paper reports on investigating the cyclic behavior of GFRP-reinforced precast FRC tunnel lining segments. Four full-scale GFRP-reinforced PCTL segments were fabricated and tested under quasi-static cyclic flexural loading. The segments had a total length, width, and thickness of 3,100, 1,500, and 250 mm, respectively. The investigated test parameters were the concrete type, the longitudinal reinforcement ratio, and the transverse reinforcement configuration. The hysteresis response, cracking pattern, ductility index, deformability, unloading stiffness degradation, and secant stiffness damage index of the test segments were identified and evaluated. The experimental results from this study showed that the hysteretic response of the GFRP-reinforced precast FRC tunnel lining segments exhibited stable cyclic behavior with no or limited strength degradation until failure. Moreover, the test results showed that the segments demonstrated adequate ductility index and deformability limits. An analytical model to predict the hysteresis behavior of the test segments was produced, and its results were compared to the experimental results. The results of this study showed the effectiveness of using FRC for GFRP-reinforced PCTL segment applications under quasi-static cyclic flexural conditions.
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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) | 0.000 | 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".