Affordable wall panels using sustainable waste materials: a review
Bibliographic record
Abstract
With the enormous population growth in the last few decades, there is a demand for infrastructure development and rapid urbanization that result in the depletion of natural resources, emission of greenhouse gases, and subsequently, exacerbation of the climate crisis. Moreover, waste materials generated by different industries such as the construction industry end up by burning or dumping them in landfills further posing serious health hazards. Besides, skyrocketing prices of housing and limited income of major population groups have resulted in the housing crisis. Therefore, it is imperative to find low-cost, environment friendly and sustainable solutions to mitigate aforementioned problems. The literature indicates that the modular construction method could be a viable solution that can reduce waste generation and construction costs. This method has been extensively used in many parts of the world in different applications mostly in the construction of low-rise buildings. However, with the advent of technological advancement in the construction industry, studies have shown that modular construction can also be successfully employed for medium and high-rise buildings. This paper presents a holistic review of the existing literature on the development of modular wall panels to foster sustainability and alleviate the housing gap. To this end, a proactive approach has been undertaken to identify key research areas to study the use of waste materials in the development of modular wall panels. The results of the literature review revealed that modular wall panels have the potential to substantially reduce the construction cost and carbon footprint. The barriers to the growth of modular construction were also discussed in this paper.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".