The Effect of Replacing Fine Silica with Fine Phosphate Waste (Russaifa mine) on the Compressive Strength of Mortar and Concrete: A Case Study in Jordan
Bibliographic record
Abstract
It is known that the dumping of Phosphate wastes from Phosphate factories and mines has a negative effect on the environment. In an effort to reduce dumping, this study examines the possible reuse of this waste as a replacement for the fine sand of silica in mortar and concrete. Phosphate waste replaces silica with the following by-weight percentages: 0%, 10%, 25%, 50% and 100%. To check the feasibility of such reuse, 30 mortar cubes, 30 concrete cubes, and 20 concrete cylinders were prepared for testing to achieve a compressive strength of 25 MPa according to ASTM (211.1-81). The tests performed in this paper are conducted to the following samples: (50 * 50 * 50 mm) mortar samples, (150 * 150 * 150 mm) concrete cubes, and (150 * 300 mm) concrete cylinders. The samples were left in curing for a period of 7 days for some samples, and others for 28 days. The results show that the use of Phosphate wastes increased the compressive strength of mortar by 29%. In concrete cubes, the use of Phosphate wastes increased compressive strength by 26%. In concrete cylinders, the use of Phosphate wastes increased the compressive strength by 34%. Subsequently, it is proposed that the stone squanders of Phosphate be utilized as an alternative to fine silica, and they demonstrated their quality through the basic tests of aggregate. The increase in stone strength is attributed to Phosphate waste as it has less absorption. The increase in the strength of Phosphate sand is due to the presence of chemical substances that increase the strength of its cohesion, such as TCP (Tricalcium Phosphate) (40.72%), P2O5 (Phosphate pentoxide) (18.64%), CaO (Calcium oxide) (28.22%) and SiO2 (Silicon dioxide) (44.45%). The percentage of CL (Chlorine) is minimal (0.01%).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".