Comparing laboratory dynamic modulus values with long term pavement performance predictions

• Main Authors: A. S. M. Asifur Rahman, Rafiqul A. Tarefder
• Format: Article
• Language: English
• Published: Vilnius Gediminas Technical University 2014-12-01
• Series: Engineering Structures and Technologies
• Subjects: asphalt concrete; dynamic modulus; mastercurve; long term pavement performance; hot-mix asphalt; shift factor
• Online Access: https://journals.vgtu.lt/index.php/EST/article/view/3203

This study compares laboratory dynamic modulus value of Superpave mixes with the dynamic modulus obtained from Long Term Pavement Performance (LTPP) database. The comparison shows that the dynamic modulus from LTPP database, which were determined by using different types of artificial neural network (ANN) models, differs from the laboratory tested dynamic modulus. The dynamic modulus data of five LTPP test sections are considered. Mixes similar to those five sections were collected from the field and tested in the laboratory. Based on the findings of this study, it can be said that dynamic modulus from ANN models are less than the laboratory dynamic modulus for New Mexico Superpave mixes. Therefore, as an important design parameter, the use of dynamic modulus predicted from Neural Network models can result in outcomes different from those using laboratory dynamic modulus.