Valorizing Recycled Concrete Aggregate as Base and Subbase for Quebec’s Roadways
Bibliographic record
Abstract
This research investigates the feasibility of using recycled concrete aggregate (RCA) in pavement construction applications throughout Quebec, with the aim of promoting sustainable construction practices and expanding the implementation of recycled materials in road construction. The study examines six distinct RCA samples sourced from different suppliers including Lafarge Company and Eurovia Quebec. A comprehensive experimental program was conducted to evaluate the physical and mechanical properties of these materials, including particle shape analysis, gradation, specific gravity, water absorption, bulk density, and Micro-Deval abrasion resistance. Special attention was given to the washing cycle analysis, where samples underwent four sequential washing cycles to evaluate fine particle content and material stability. Additionally, infiltration rate testing using a modified double-ring infiltrometer was conducted to assess drainage capacity, a crucial characteristic for pavement applications in Quebec's climate. All tests were performed in accordance with ASTM standards and evaluated against the Ministry of Transportation of Quebec (MTQ) specifications. Results indicate that properly processed RCA can achieve physical and mechanical properties suitable for pavement applications, particularly in base and subbase layers. The samples demonstrated bulk densities ranging from 980 to 1400 kg/m³ and Micro-Deval losses between 14.4% and 20.2%. Water absorption values varied from 2.2% to 12.8%, while specific gravity remained consistent across all samples (2.69-2.76). Infiltration rates showed significant variation between treated (210-260 cm/h) and untreated (60 cm/h) samples, correlating strongly with fine content and processing methods. Additionally, a survey was conducted among key stakeholders in Quebec's construction industry to assess current practices and barriers. The study concludes that with appropriate quality control measures and processing methods, RCA can serve as an effective alternative to natural aggregates in road construction, successfully balancing sustainability goals with performance requirements while maintaining high-quality standards.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".