Experimental Characterization of Strength of Self Curing Concrete
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Bibliographic record
Abstract
Today concrete is most widely used construction material due to its good compressive strength and durability. Depending upon the nature of work the cement, fine aggregate, coarse aggregate and water are mixed in specific proportions to produce plain concrete. Plain concrete needs congenial atmosphere by providing moisture for a minimum period of 28 days for good hydration and to attain desired strength. Any laxity in curing will badly affect the strength and durability of concrete. Self-curing concrete is one of the special concretes in mitigating insufficient curing due to human negligence paucity of water in arid areas, inaccessibility of structures in difficult terrains and in areas where the presence of fluorides in water will badly affect the characteristics of concrete. The present study involves the use of shrinkage reducing admixture polyvinyl alcohol in concrete which helps in self curing and helps in better hydration and hence strength. In the present study, the effect of self curing agent on compressive strength is examined by addition of varying percentage of PVA & Rice Husk Ash. PVA mixed in water from 0.5%,1%,2%,3%,4% & 5% by weight of cement. It was found that PVA could help in self curing by giving strength on par with conventional curing. It was also found that 3% of PVA by weight of cement was optimum for M20 grade concretes for achieving maximum strength (compressive nature) without compromising workability. Rice Husk Ash mixed in water from 5%,10%,15% & 20% by weight of cement. It was found that Rice Husk Ash could help in self curing by giving strength on par conventional curing .It was also found that 10% of Rice Husk Ash by weight of cement was optimum for achieving maximum strength. In this Paper to study the determing Modulus Of Elastcity Of Self Curing Concrete. Key words: Self curing agent, PVA, Rice Husk Ash, Admixtures, drying shrinkage.Water Retention.
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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