The Influence of Heating Temperature on Aggregates Made from Expanded Polystyrene on the Mechanical Behaviors of Lightweight Concrete
Bibliographic record
Abstract
The use of lightweight materials is currently increasing because it is able to reduce the weight of structures and, of course, will provide a smaller seismic load.Efforts to minimize the burden of lightweight materials can be achieved by substituting conventional aggregates with lighter alternatives, such as EPS.The utilization of EPS not only helps in reducing structural loads but also serves as a solution to address plastic waste pollution.This study aims to improve the quality of lightweight concrete using pumice sand and aggregates from EPS waste.The concrete quality was improved by improving the aggregate performance of EPS waste by heating.Heating of EPs waste aggregates was carried out at temperature variations of 100℃, 110℃, 120℃, 130℃, 140℃.The composition of the cement-soil mixture was made in volume ratios of: 1 part cement, 2 parts pumice sand and 3 parts modified EPS aggregate with a water cement ratio of 0.45.The quality tests carried out include compressive strength test, tensile strength test and collapse modulus test.The results of this study indicate that the increase in EPS density due to the applied heating has an impact on the improvement of the mechanical parameter values of lightweight concrete.
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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".