Impact of Fly Ash on Time-Dependent Properties of Agro-Waste Lightweight Aggregate Concrete
Bibliographic record
Abstract
The utilization of by-products and waste materials to substitute for the natural or manufactured resources is considered as a practical way to obtain green building materials. In concrete mixtures, amongst the many available options, Fly Ash (FA) as a by-product pozzolan has been used as a partial replacement of cement. As for the aggregates, lightweight agro-waste oil palm shell (OPS) can be used as a replacement to conventional aggregate for the production of lightweight aggregate concrete. The present communication aims to investigate the impact of FA on time-dependent development properties of OPS lightweight aggregate concrete, including density, water absorption, compressive strength up to 120-days, and drying shrinkage up to the age of 365-days under standard moist curing, partially early curing, and non-curing conditions. Additionally, drying shrinkage crack development was investigated. In this study, two series of concrete mixtures with different substitution levels of OPS (0%, 50%, and 100%) and FA were tested. From the obtained results, it was concluded that the incorporation of fly ash in OPS concrete reduces the density and compressive strength values. Dually, the initial and final water absorption values plus the rate of drying shrinkage at early and long-term ages increased. On top of that, a high potential of drying shrinkage crack, especially for mixtures with 100% OPS, was identified.
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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".