Transverse reinforcement configurations in GFRP-reinforced concrete columns: Experiments and damage mechanics-based modeling
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Bibliographic record
Abstract
The effects of transverse reinforcement configurations on the strength and deformability of concrete columns reinforced with glass fiber-reinforced polymer (GFRP) bars and ties were studied, with emphasis on post-peak performance. A new experimental method exposed columns without concrete cover to directly observe the failure modes of longitudinal and transverse GFRP bars. The experiments were supported by 3D finite element (FE) models using concrete damage plasticity (CDP) for concrete and the LaRC05 failure criteria for GFRP bars. The findings reveal that reducing the tie spacing from 12 d b to 6 d b ( d b is the longitudinal bar's nominal diameter) increased the deformability index from 0.25 to 0.8 and enhanced post-peak load retention from 0.001 μm/m to 0.011 μm/m. Increasing the tie overlap length from 20 d t to 28 d t ( d t is the tie's nominal diameter) improved confinement, delaying bar buckling and increasing second peak load by 17 %. Additionally, using fasteners at 3 d t intervals on tie overlaps maintained tie integrity post-peak, ensuring more stable behavior. Large-scale tests from the literature were analyzed and categorized into three deformability classes based on axial load-displacement and stress-strain behavior. A deformability index, I AD , was proposed, showing a linear relationship with the transverse reinforcement ratio, ρ t , with a coefficient of determination (R 2 ) of 0.84. A comparative analysis of FEM approaches for modeling GFRP-RC columns further validated these findings. • A test method was developed to closely monitor column behavior with exposed reinforcement. • Advanced FEM analysis was used to capture damage in concrete and 3D bars and was compared with a common simpler method. • Optimal tie spacing, overlap lengths, and fastener intervals are recommended to enhance column deformability. • A new deformability index predicts post-peak behavior in load-displacement and stress-strain curves.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it