1401 N. Pine St., Rolla, MO 65409

Ahmed El-Ashwah, a doctoral candidate in civil engineering, will defend their dissertation titled “Optimizing Frictional Performance of Rap-Recycled Asphalt Mixtures: Material Selection and Design Considerations.” Their advisor, Dr. Magdy Abdelrahman, is the Missouri Asphalt Pavement Association Professor in the civil, architectural and environmental engineering department. The dissertation abstract is provided below.

Pavement skid resistance is paramount for road safety, particularly under wet conditions, as it enhances tire-road surface interaction and mitigates accident risks. Concurrently, the emphasis on sustainability in asphalt pavement construction has led to the increased use of recycled components, such as Reclaimed Asphalt Pavement (RAP) materials and crumb rubber (CR). However, incorporating RAP materials into Stone Matrix Asphalt (SMA) mixtures raises concerns about decreased frictional resistance and a heightened risk of early cracking and moisture damage. This underscores the necessity of thorough friction testing, given that low-friction aggregates from RAP materials, originally used in non-SMA mixtures or local roads, could increase crash risks when incorporated into SMA mixtures.
This study aimed to evaluate the impact of incorporating recycled components, particularly RAP material and engineering crumb rubber (ECR), on the frictional performance of SMA mixtures through extensive laboratory testing. Additionally, dense-graded (DG) mixtures were investigated to understand the impact of different mix designs on the friction properties of asphalt pavement. Initially, the morphological characteristics of recovered RAP and raw aggregates were examined at various Micro-Deval (MD) run times using the Aggregate Imaging Measurement System (AIMS), the British Pendulum Tester (BPT), and the Dynamic Friction Tester (DFT). Subsequently, the microtexture and macrotexture of laboratory-produced slabs were evaluated using the DFT and a Circular Track Meter (CTMeter). A three-wheel polishing device (TWPD) was also employed to simulate traffic-induced polishing. Furthermore, a simple testing procedure was proposed, adopting the BPT in conjunction with a British/accelerated polishing wheel to assess the friction properties of asphalt mixtures.
The analysis of testing results was conducted using multiple statistical methods to ensure robustness and reliability. Analysis of Variance (ANOVA) was employed to determine significant differences in friction properties under various test conditions. Pearson's Correlation Coefficient (PCC) matrix was utilized to explore relationships between various measured properties, such as aggregate shape, texture, and friction, identifying which aggregate characteristics most strongly correlated with friction performance. Additionally, Random Forest Analysis (RFA) was implemented to ascertain the significance of each aggregate property, identifying the most critical factors contributing to asphalt pavement friction degradation.
The findings revealed that the frictional performance of SMA mixtures improved significantly with the incorporation of RAP materials by approximately 15% and ECR by about 12.5%. The RFA model demonstrated high predictive accuracy, with an R² value of 0.97 for the training dataset and 0.86 for the testing dataset. These results underscore the potential of RFA in predicting friction loss and inform the development of a framework for asphalt mix design that supports both sustainability and road safety objectives. Additionally, a framework considering the hierarchical structure of inputs was developed to predict the asphalt pavement skid resistance in terms of mixture components properties, giving a chance to optimize the blending of RAP-recycled asphalt mixture components and mix design to achieve the desired friction properties of asphalt mixtures cost-effectively.

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