Experimental Analysis on Mechanical Performance of Recycled Concrete Made from Polypropylene Fiber and Artificial Sand
Bibliographic record
Abstract
This paper aims to disclose the working performance and mechanical performance of recycled concrete made from polypropylene fiber and artificial sand (P-RCAS). Taking fiber content and concrete strength as variables, a total of 90 P-RCAS cubes and prisms were designed and prepared for axial loading tests. The working performance of the P-RCAS was tested, the failure process and failure mode of the specimens were observed, and the compressive strengths of cubs and prisms were measured. Moreover, the authors probed deep into how fiber content affect the working performance and mechanical performance of the P-RCAS. The results show that adding polypropylene fiber into the artificial sand recycled concrete (RCAS) can produce concrete with good workability; the additional fibers help to enhance the compressive strength of RCAS specimens on all strength levels, but the enhancement was insignificantly for specimens on high strength levels. Finally, the test data were used to fit the calculation formulas for fiber content, water-cement ratio, and compressive strength, as well as the relationship between axial compressive strength and cube compressive strength. The research results provide reference for further research and engineering application of the RCAS.
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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) | 0.001 | 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".