Usage of polystyrene disposable food dishes in the lightweight concrete making
Bibliographic record
Abstract
Abstract The increasing use and subsequent accumulation of polystyrene containers has triggered a substantial environmental problem. This study investigated using varied percentages of solid waste polystyrene disposable food dishes in the production of lightweight concrete samples with 350 kilograms per cubic meter (kg/m3) of cement and a density of 1,300 kg/m3. The polystyrene disposable dishes were ground into beads of 0–3 millimeters (mm) and 3–6 mm in size. First, the characteristics of Type II Portland cement, polystyrene, and aggregates were examined. The following characteristics of concrete using ASTM International and British Standards Institution standards were tested: slump, compressive strength, ability to resist chloride ion penetration, and resistance of concrete to rapid freezing and thawing cycles. Scanning electron microscopy (SEM) and energy dispersive X‐ray spectroscopy analytical techniques were also used. The slump of samples varied between 40 and 70 mm and was not dependent on either the polystyrene percentage or the size of the polystyrene beads in the concrete samples (p‐value > .05). The compressive strength of the concrete samples after 90 days of curing, and using different percentages of polystyrene, varied between 96 and 113 kilograms per square centimeter (kg/cm2). The resistance of the samples to the freezing and thawing cycle and chloride ion penetration were affected unfavorably by the presence of the polystyrene. The SEM technique indicated that concrete samples containing 15% and 25% polystyrene had denser crystals and less void than concrete samples with 40% and 55% polystyrene.
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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".