Devulcanized Rubber a Solution for Scrap Tire
Bibliographic record
Abstract
Waste is a major issue around the world with approximately 2.01 billion ton of waste generated annually. which can be Rubber waste from tires is known to be a massive environmental risk to the environment as it is non-biodegradable. However, rubber is an indispensable material of the technological development, from the simplest balloon to the complex rocket propellant. The majority of tires waste are dealt with a non-environmental manner, either dumped in landfills or burnt causing negative impact on human health and environment. Unfortunately, one of the largest tires landfill in the world is located in the state of Kuwait, AlRuhayah. This site host around 50 million dead tires. This study investigates the proper waste management of accumulate tires in Kuwait based on cost, profitability, environmental impact, efficiency, net energy produced, and operation and maintenance. A comparison between reusing, rethreading, pyrolysis, mechanical grinding and devulcanization methods were applied to seek the best method for tire waste management. Out of the eight adequate methods, devulcanization was the superior option due to its efficiency, profitability and least impact on environment. Precise calculations were made concerning different aspects such as transportation, structure and expenses. The total amount of revenue for this 10-year project is $75 million US Dollars and annually produce 24 million kg of rubber. This rubber can be further processed into green concrete, pavements and aerogel. The adaption of the proposed method is of great importance to regulatory bodies to regulate and reduce the tire waste and hence improve the environment and human health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".