Structural Performance of Polymer Fiber Reinforced Engineered Cementitious Composites Subjected to Static and Fatigue Flexural Loading
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Bibliographic record
Abstract
This paper presents the influence of silica sand, local crushed sand and different supplementary cementing materials (SCMs) to Portland cement (C) ratio (SCM/C) on the flexural fatigue performance of engineered cementitious composites (ECCs). ECC is a micromechanically-based designed high-performance polymer fiber reinforced concrete with high ductility which exhibits strain-hardening and micro-cracking behavior in tension and flexure. The relative high cost remains an obstacle for wider commercial use of ECC. The replacement of cement by SCMs, and the use of local sand aggregates can lower cost and enhance greenness of the ECC. The main variables of this study were: type and size of aggregates (local crushed or standard silica sand), type of SCMs (fly ash “FA” or slag), SCM/cement ratio of 1.2 or 2.2, three fatigue stress levels and number of fatigue cycles up to 1 million. The study showed that ECC mixtures produced with crushed sand (with high volume of fly ash and slag) exhibited strain hardening behavior (under static loading) with deformation capacities comparable with those made with silica sand. Class F-fly ash combined with crushed sand was the best choice (compared to class CI fly ash and slag) in order to enhance the ECC ductility with slag–ECC mixtures producing lowest deflection capacity. FA–ECC mixtures with silica sand developed more damage under fatigue loading due to higher deflection evolution than FA–ECC mixtures with crushed sand.
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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 | 0.000 | 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 it