Effect of Aqua Heat Treatment on the Mechanical, Durability and Water Resistance Performance of Rubberized Sand Concrete
Bibliographic record
Abstract
The exponential growth in vehicle tire production has resulted in a substantial accumulation of rubber waste, raising serious environmental issues due to its resistance to decomposition.To address this issue, the current investigation sheds light on the use of crumb rubber (CR) as a partial substitute for fine aggregates in sand concrete, applied at varying dosages (0%, 3%, 6%, 9%, and 12%).The primary objective is to enhance the durability of sand concrete, particularly its resistance to water penetration, which is critical for maintaining structural integrity in aggressive environments.The influence of both untreated and aqua heat-treated rubber on the physical and mechanical properties of sand concrete was systematically investigated.Workability, density, compressive and flexural strengths, porosity, and water absorption were evaluated Additionally, Scanning Electron Microscopy (SEM) analysis was conducted to characterize the microstructural modifications induced by aqua heat-treated rubber particles.The results demonstrated that the incorporation of heat-treated rubber improved water penetration resistance by up to 9% compared to concrete containing untreated rubber.Nonetheless, both untreated (UTR) and treated rubber (TR) caused a reduction in density and workability.While the initial inclusion of rubber increased porosity and water absorption, these adverse effects were significantly mitigated over time through aqua heat treatment.Overall, the optimal content of aqua-heat -treated rubber powder was identified as 3%, yielding the most favorable balance between workability, water absorption, porosity and mechanical performance.
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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".