Influence of Waste Cork with Thinner on the Rheological Properties of Asphalt
Bibliographic record
Abstract
Over the last two decades, the rapid and continued deterioration of the transportation network has been regarded as a major issue. There are many measures that can be taken to reduce this deterioration and improve road specifications, including improving road design, using higher quality materials, and using more efficient construction methods. This study is concerned with three principles: including investigating the impact of using waste paste on the rheological properties of bitumen; the environmental pollution that is a global problem; and the economic benefits as a result of the reusing of waste materials such as corks to produce new reusable materials like Modified-Asphalt. In this research, cork has been melted by thinner and mixed with asphalt to get a good paste with weight percentages of 1%, 3%, 5%, and 7%. After conducting the necessary tests on the samples, it was found that the addition of waste paste to virgin bitumen has softened the bitumen by decreasing the hardness and adhesiveness of the bitumen by increasing penetration with increasing cork paste content. The findings show that the current procedure can be used in cold regions because it requires less hard asphalt than that used in hot regions. It can also be used with natural asphalt, like natural rock asphalt, in various percent to give asphalt with suitable properties for use in roofing and paving roads.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 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".