Mineral Slag used as an Alternative of Cement in Concrete
Bibliographic record
Abstract
This paper summarizes the results of experimental studies carried out at Zhengzhou University, school of Mechanics and Engineering Science, research laboratory, on the performance of concrete produced by combining ordinary Portland cement (OPC) with ground-granulated blast furnace slag (GGBS).Concrete specimens cast with OPC and various percentage of GGBS (0%, 30%, 50%, and 70%) were subjected to high temperature exposure and extensive experimental test reproducing basic freeze-thaw cycle and a chloride-ion attack to determine their combined effects within the concrete samples.From the experimental studies comparisons were made on the physical, mechanical, and microstructural properties in compassion with ordinary Portland cement concrete (OPC).Further, durability of GGBS cement concrete such as exposure to chloride ion attack and freeze-thaw action in compassion with various percentage of GGBS and ordinary Portland cement concrete of similar mixture composition were analyzed.The microstructure, mineralogical composition, and pore size distribution of concrete specimens were determined via Scanning electron microscopy analysis (SEM), and X-ray diffraction (XRD).The result demonstrated that when the exposure temperature increases from 200 ºC to 400 ºC, the residual compressive strength was fluctuating for all concrete group; and compressive strength and chloride ion exposure of the concrete decreased with the increasing of slag content.The SEM and EDS results showed an increase in carbonation rate with increasing of slag content.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".