Concrete with Organic Waste Materials as Aggregate Replacement
Bibliographic record
Abstract
The disposal of high volumes of organic waste is a global issue. Using organic waste instead of sand as an aggregate material for concrete could reduce the strain on waste treatment processes and on the extraction of finite resources. At the same time, it could be a climate change mitigation strategy, by storing the biogenic carbon contained in the organic waste. This project investigated the viability of replacing 10% of fine aggregate in concrete with various organic waste materials, namely rice husk ash, wood ash, corncob granules, and wheat straw. The fresh concrete’s properties were studied using the slump test, and the hardened concrete’s mechanical properties were measured using the compressive strength and flexural strength tests. In this study, 14 days of curing were considered for the mechanical tests, although the 28-day mechanical strength is more generally accepted. The mechanical performances along with a life cycle assessment (LCA) comparison between the concrete with organic waste and traditional concrete were conducted. The results suggested that rice husk ash and wood ash are the most-suitable organic waste products for use as aggregate replacers considering the mechanical properties. The concrete samples incorporating wheat straw and corncob granules exhibited relatively low strength; unless advanced treatment methods are applied to enhance the concrete’s performance, the utilization of these organic wastes in concrete may be limited. The environmental impact assessment of traditional concrete shows that the main contributor to almost every impact category is the production of Portland cement. Sand production contributes only marginally to the overall impact of the concrete. In terms of life-cycle greenhouse gas (GHG) emissions, traditional concrete exhibits the lowest GWP impact per cubic meter when mechanical properties are included in the functional unit used for the comparison. Nevertheless, concrete samples with wood ash and rice husk ash partially offset their lower compressive strength with higher carbon sequestration, showing a similar GWP impact to traditional concrete. This makes them promising alternatives, especially for cases where limited compressive strengths are needed. Further investigations to improve their mechanical properties and optimize their performance are warranted.
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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 | 0.001 |
| 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".