Effect of surface profile on the bond strength of lap spliced GFRP bars in concrete beams
Bibliographic record
Abstract
The splice strength of new-generation GFRP bars with various surface profiles has been insufficiently studied in the literature. This paper investigates the bond between new-generation GFRP bars and concrete using the lap splice test method. The experimental program consisted of 12 full-scale reinforced concrete beams, each reinforced with spliced GFRP bars featuring ribbed, sand-coated, and grooved surface profiles, without transverse reinforcement in the splice zone. In addition to the surface profile effect, the effects of bar diameter and splice length on bond strength are assessed. Beams with No. 6 bars showed higher bond strength than those with No. 8 bars, with ratios of 1.14 and 1.07 for sand-coated and ribbed bars, indicating a greater size effect for sand-coated bars. Beams with spliced ribbed GFRP bars showed, on average, 7 % lower normalized bond strength than sand-coated and grooved bars, with minimal surface profile impact at a longer, more practical splice length. The bond strength of sand-coated and grooved bars remained identical. A dataset of 205 experimental tests was compiled to evaluate the reliability of existing bond strength equations, including those specified in ACI CODE-440.11–22 and CSA S806–12 (R2021). An equation was proposed to estimate bond strength. The proposed equation exhibited better prediction accuracy compared to existing models across all specimen categories, including the entire dataset, specimens without transverse reinforcement in the splice zone, those with transverse reinforcement, and lap splice beams. The proposed equation achieved an RMSE of 111.9 MPa on the entire dataset, outperforming ACI 440.11–22 (142.4 MPa) and CSA S806–12 (142.99 MPa). • The bond strength of new-generation GFRP bars was investigated. • Twelve full-scale beams with ribbed, sand-coated, and grooved bars were tested. • Ribbed bars showed slightly lower bond strength than sand-coated and grooved bars. • A dataset of 205 tests was compiled to assess the reliability of bond models. • Proposed equation achieved higher prediction accuracy than existing bond models.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".