Life Cycle Analysis of Light Weight Artificial Aggregates for Sustainable Construction
Bibliographic record
Abstract
This article focuses on a comprehensive life cycle analysis (LCA) of granules derived from fly ash, marble sludge, and cement in various proportions, with the aim of evaluating their viability as a sustainable resource in the construction activities.The investigation delves into the environmental and economic implications of incorporating artificial granules into construction materials, examining their entire life cycle from production to disposal.Encompassing extraction of resources, building, transporting, manufacturing procedures, and end-of-life circumstances, the analysis sheds light on key factors such as energy consumption and resource depletion.In recent years, the construction sector has increasingly embraced recycled materials, with lightweight artificial aggregates emerging as a promising alternative to traditional concretes.This study introduces a selection model for lightweight artificial aggregates through experimental processes, considering economical, ecological, and technological elements.Three distinct mixtures, incorporating cement and industrial waste such as fly ash from a municipal waste incineration plant and marble sludge, were prepared.With a consistent 75% fly ash inclusion, varying percentages of marble sludge (10%, 15%, 20%) and cement (15%, 10%, 5%) were employed.This approach facilitated a comprehensive evaluation of the economical, ecological, and mechanical features of every lightweight artificial aggregate blend.The paper identifies preferred scenarios among the three mixtures, aiming for convergence and compliance in terms of environmental impacts (assessed through Life Cycle Assessment), economic considerations (assessed utilizing Life Cycle Costing), and technical-functional aspects.The findings underscore that the optimal solution for sustainable lightweight artificial aggregates involves a composition of 75% fly ash, 15% marble sludge, and a higher cement content of 10%.This outcome emphasizes the practicality of making environmentally conscious choices in selecting lightweight artificial aggregates for construction applications, aligning with the industry's shift towards sustainability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".