Case Study on the Effect of Recycled Asphalt Layer Parameters on the Bearing Capacity of the Pavement




artificial neural network (ANN), base damage index (BDI), compressive strength, FWD, pavement testing, reclaimed asphalt pavement (RAP), recycled asphalt, resilient modulus


Numerous ways to use recycled asphalt (RA) in the road base course will provide both environmental and economic benefits, allowing to recycle and utilise this initially waste material in road or pavement reconstruction projects. However, the properties and parameters of RA necessary for the application of reclaimed asphalt pavement (RAP) in a new pavement structure in most cases are not detectable in the design stage, which complicates design and construction process. The purpose of this paper is to study possibilities for evaluating the performance and parameters of RA, as well as to review the possibilities, methods and applications for RA testing. Data for this case study were obtained from recently completed road structures in the form of FWD measurements, together with lab explored parameters of drilled pavement cores. Based on that data, the relationships between the main pavement structural parameters, such as modulus on the surface of the pavement, compressive strength of RA core segment, thickness of bound layers and back calculated modulus were examined. On the way to exploring different analytical approaches, two approximation models were developed and compared, using the obtained data: by directly approximating the obtained data and after processing them with artificial neural network (ANN).


Abo-Hashema, M. (2009). Artificial Neural Network Approach for Overlay Design of Flexible Pavements. The International Arab Journal of Information Technology, 6(2), 204–212.

Anthonissen, J., Van den Bergh, W., & Braet, J. (2016). Review and Environmental Impact Assessment of Green Technologies for Base Courses in Bituminous Pavements. Environmental Impact Assessment Review, 60, 139–147.

Bleakley, A. M., & Cosentino, P. J. (2013). Improving Properties of Reclaimed Asphalt Pavement for Roadway Base Applications Through Blending and Chemical Stabilization. Transportation Research Record, 2335(1), 20–28.

Chen, D.-H., Bilyeu, J., Lin, H.-H., & Murphy, M. (2000). Temperature Correction on Falling Weight Deflectometer Measurements. Transportation Research Record, 1716(1), 30–39.

Huang, B., Shu, X., & Burdette, E. G. (2006). Mechanical Properties of Concrete Containing Recycled Asphalt Pavements. Magazine of Concrete Research, 58(5), 313–320.

Lee, I.-M., Kim, J.-S., Yoon, H.-K., & Lee, J.-S. (2014). Evaluation of Compressive Strength and Stiffness of Grouted Soils by Using Elastic Waves. Scientific World Journal, 2014, 1–9.

Noguchi, T., & Nemati, K. M. (2007). Relationship between compressive strength and modulus of elasticity of high-strength concrete. In Proceedings of the 6th International Conference on Fracture Mechanics of Concrete and Concrete Structures.

Silva, R. V., De Brito, J., & Dhir, R. K. (2016). Establishing a Relationship Between Modulus of Elasticity and Compressive Strength of Recycled Aggregate Concrete. Journal of Cleaner Production, 112(4), 2171–2186.

Tabaković, A., Gibney, A., McNally, C., & Gilchrist, M. D. (2010). Influence of Recycled Asphalt Pavement on Fatigue Performance of Asphalt Concrete Base Courses. Journal of Materials in Civil Engineering, 22(6), 643–650.

Trtnik, G., Kavčič, F., & Turk, G. (2009). Prediction of Concrete Strength Using Ultrasonic Pulse Velocity and Artificial Neural Networks. Ultrasonics, 49(1), 53–60.




How to Cite

Zariņš, A. (2020). Case Study on the Effect of Recycled Asphalt Layer Parameters on the Bearing Capacity of the Pavement. The Baltic Journal of Road and Bridge Engineering, 15(5), 45-58.