Effects of Medium Temperature and Industrial By-Products on the Key Hardened Properties of High Performance Concrete
Bibliographic record
Abstract
The aim of the work reported in this article was to investigate the effects of medium temperature and industrial by-products on the key hardened properties of high performance concrete. Four concrete mixes were prepared based on a water-to-binder ratio of 0.35. Two industrial by-products, silica fume and Class F fly ash, were used separately and together with normal portland cement to produce three concrete mixes in addition to the control mix. The properties of both fresh and hardened concretes were examined in the laboratory. The freshly mixed concrete mixes were tested for slump, slump flow, and V-funnel flow. The hardened concretes were tested for compressive strength and dynamic modulus of elasticity after exposing to 20, 35 and 50 °C. In addition, the initial surface absorption and the rate of moisture movement into the concretes were determined at 20 °C. The performance of the concretes in the fresh state was excellent due to their superior deformability and good segregation resistance. In their hardened state, the highest levels of compressive strength and dynamic modulus of elasticity were produced by silica fume concrete. In addition, silica fume concrete showed the lowest level of initial surface absorption and the lowest rate of moisture movement into the interior of concrete. In comparison, the compressive strength, dynamic modulus of elasticity, initial surface absorption, and moisture movement rate of silica fume-fly ash concrete were close to those of silica fume concrete. Moreover, all concretes provided relatively low compressive strength and dynamic modulus of elasticity when they were exposed to 50 °C. However, the effect of increased temperature was less detrimental for silica fume and silica fume-fly ash concretes in comparison with the control concrete.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".