Off-axis mechanical properties of AR-glass textile reinforced engineered cementitious composite: Experimental and theoretical study
Bibliographic record
Abstract
AR-Glass Textile Reinforced Engineered Cementitious Composite (GTR-ECC) is widely utilized in structural strengthening owing to its excellent mechanical properties. However, its behavior under off-axis loading remains unclear. This paper investigates the mechanical properties of GTR-ECC under off-axis tensile loading, along with its constituent materials. Results show that GTR-ECC exhibits improved first-crack stress and ultimate strength compared to plain ECC. Notably, the enhancement ratios for these properties under off-axis angles (15°, 30°, 45°) were significantly higher than those observed in the 0° case. This is attributed to the dual effects of the textile: reinforcement from the textile itself and weakening due to the cross-sectional voids it creates. At 0°, the weft yarns create penetrating voids, resulting in a more pronounced weakening effect compared to other angles. Crack distribution in GTR-ECC was similar to ECC, with widths of 60–120 μm, confirming effective synergy between textile and matrix. Furthermore, a modified rule-of-mixtures model is proposed, which incorporates both the reinforcing and weakening effects of the textile, enabling the prediction of the off-axis tensile performance of GTR-ECC based on the properties of its constituent materials. The model shows high accuracy, with average errors of 5.31 % for first-crack stress, 5.96 % for peak strength, and a Global CMAD of 4.51 %. This study provides experimental insights into the mechanical behavior of GTR-ECC under varying off-axis angles and proposes a precise micromechanical model, establishing a foundation for the application of GTR-ECC under complex loading conditions.
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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".