Development and Evaluation of Crumb Rubber-Modified Binders for High-Performance Asphalt Concrete
Bibliographic record
Abstract
Asphalt pavements, or asphalt concrete (AC), are viscoelastic composites designed for modern transportation but often exceed their design limits, leading to distresses like rutting, moisture damage, and cracking. To address these issues, high-modulus asphalt concrete (HMAC) was developed in France in the 1960s as enrobé à module élevé (EME), using stiff asphalt binders to enhance rutting and moisture resistance. However, increased stiffness reduces stress dissipation, making HMAC prone to fatigue and thermal cracking, a primary concern in cold regions like Canada, where extreme temperature fluctuations accelerate pavement deterioration. This thesis explores a novel approach to pavement design that addresses the limitations of hard-grade asphalt binders in HMAC, particularly in cold climates. By incorporating crumb rubber-modified binder (CRMB), a sustainable and performance-enhancing alternative, this research aims to develop high-performance asphalt concrete (HPAC). This advanced mixture retains or improves the superior dynamic stiffness of HMAC while significantly improving cracking resistance, ensuring long-term durability. Additionally, HPAC is tailored explicitly for base course applications in full-depth asphalt pavements, where tensile and compressive stresses are at their highest. Moreover, this research incorporates a comprehensive asphalt binder modification technique using a crumb rubber modifier (CRM) and its effect on AC mixtures regarding resistance to prevalent pavement distresses, such as rutting, moisture damage, and cracking. The study is divided into five key sections. The first section introduces asphalt pavement technologies, highlighting advancements and the challenges posed by increasing traffic loads and climate change, along with the study’s objectives and methodology. The second section reviews existing literature on AC design methodologies, the rheological behaviour of conventional and modified binders, and the evolution of HMAC to HPAC. This review identifies research gaps from relevant literature and emphasizes the need for HPAC solutions suited to Canada’s extreme climatic conditions and growing traffic demands. The third section evaluates the rheological performance of CRMB by examining the effects of crumb rubber modifier (CRM) content and blending time on asphalt binder properties, notably achieving a high Performance-Grade (PG) 82 intended for HPAC application. A 30-mesh CRM was mixed into a PG 64-22 unmodified binder at varying concentrations (3%, 6%, 9%, 12%, and 15%) and blending times (30, 60, and 90 minutes) at 180°C. Results indicated a 12% CRM content with a 60-minute blending time optimized polymerization, achieving PG 82-22, demonstrated superior high-temperature performance while maintaining adequate elasticity and low-temperature stress relaxation properties. Intermediate-temperature results suggested improved fatigue resistance, while aging analysis revealed lower stiffness gains over time, indicating enhanced resistance to oxidative and physical hardening. Consequently, the optimized CRMB suitability for HPAC application was validated with the dynamic modulus test, exceeding the requirement (≥14,000MPa @10°C, 10 Hz). However, phase separation remained a challenge, emphasizing the need for improved storage stability techniques. The fourth section incorporates the optimized CRMB into AC mixtures to assess its suitability for HPAC applications through performance-based evaluations. Comparative analysis with unmodified AC confirmed that crumb rubber-modified asphalt concrete (CRMAC) mixtures demonstrated superior rutting resistance and moisture durability in the Hamburg wheel tracking (HWT) test and exhibited enhanced stress redistribution, effectively delaying crack initiation at low temperatures in the disc-shaped compact tension (DCT) test. The performance space diagram (PSD), developed within the balanced mix design (BMD) framework, further illustrated this improvement by positioning CRMAC mixtures in a more balanced performance zone and reinforcing their potential for base course applications in cold regions. The final section presents the key findings of the study, including a summary, conclusions, and future research directions. The results emphasize CRMB’s potential to enhance the durability and structural integrity of HPAC mixtures, positioning them as a promising alternative for base course layers in extreme climates. While CRMAC demonstrates significant performance improvements, further research is recommended to evaluate its long-term field performance and optimize mix designs to mitigate temperature and traffic-induced distress.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".