Effect of Recycled Asphalt Pavement on Suction and Collapse Potential of Collapsible Soils
Bibliographic record
Abstract
Recycled asphalt pavement (RAP) is a type of waste generated during the renovation of damaged roadways.It is often irresponsibly discarded in developing countries, such as Algeria, thereby causing environmental harm.Recycling RAP is an environmentally friendly technology that conserves significant natural resources and provides ecological benefits in geotechnical engineering, particularly in applications involving collapsible soils.These soils, characterized by their unsaturated nature, can undergo significant deformations when wet, whether they are subjected to a load or not.The objective of this study is to demonstrate the potential for reducing settlement risks in reconstituted soils exhibiting collapsibility.This was investigated by varying water contents (W0 = 2%, 4%, and 6%) and compaction energies (Ec = 30, 50, and 70 blows), while incorporating RAP at different contents (2%, 4%, 6%, 8%, and 10%).Suction and collapse potential (Cp) were measured to evaluate the performance of these modified soils.The results revealed improved geotechnical properties, with the collapse potential (Cp) decreasing from 14.4% to 0.4%, and suction (s) reducing from 9.89 MPa to 1.12 MPa.These improvements were associated with the development of a compacted microstructure and reduced porosity.
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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 | 0.000 | 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) | 0.001 | 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".