Experimental Investigation on Using Electrical Cable Waste as Fine Aggregate and Reinforcing Fiber in Sustainable Mortar
Bibliographic record
Abstract
Challenges posed by industrial solid waste, particularly Electrical Cable Waste (ECW), have been increasingly recognized due to their environmental implications and substantial decomposition timelines. ECW, a byproduct of aggressive demolition and reconstruction in Iraq, has seen limited investigation regarding its potential use as an aggregate substitute and fiber additive in concrete applications. This study endeavors to repurpose ECW as a partial replacement for natural sand and as fiber reinforcement, with a focus on both short-term and long-term performance. A fixed ratio of natural sand was substituted with ECW (10%), and waste fibers were integrated at varying concentrations (0.5%, 1%, 1.5%, 2%, 2.5%, and 3%). For comparative purposes, a control mix devoid of ECW and fibers was also examined. Evaluations were conducted on the flow rate, along with compressive strength, flexural strength, and density at intervals of 7, 28, and 360 days. Results indicate that despite a reduction in flowability and a decrease in hardened density to under 2000 kg/m 3 , inclusion of ECW can yield a sustainable lightweight mortar without significant compromise on strength. This study thus underscores the potential of waste repurposing as a viable solution for waste management and environmental enhancement. Additionally, this approach can help mitigate natural resource depletion, such as that of natural sand, fostering a move towards sustainable construction practices.
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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 | 0.000 |
| 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 | 0.001 | 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".