Laboratory Performance Characterization of Pavements Incorporating Recycled Materials
Bibliographic record
Abstract
This paper provides a mechanistic procedure for performance characterization of recycled aggregate systems for use as aggregate layers. Twelve recycled aggregates systems with different lithologies and known field performance histories were selected for this study. The aggregate sources were selected from seven different states with different climatic conditions to account for the environmental impacts on the performance of the pavements constructed with recycled materials. A comprehensive material testing protocol was followed to characterize the mechanical and physio-chemical properties of the recycled aggregate systems. Shear strength test at different confinement levels as well as Canadian freeze-thaw test, Micro-Deval test and tube suction test were performed on the samples. Analysis of the laboratory tests showed that several recycled systems performed equally or better compared to control systems consisting of virgin aggregates in terms of higher shear strength and higher hardening index. Laboratory test results also showed that Recycled Concrete (RC) materials typically had superior mechanical properties such as higher resilient modulus and hardening index compared to Recycled Asphalt (RA) systems, however, RC systems showed higher frost susceptibility. The laboratory analysis and numerical simulations results presented in this study underscore the significance of climatic conditions and subgrade soil type when RA system is considered as viable option.
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 | 0.001 | 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 | 0.002 |
| 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 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".