A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
Developing a Rutting Prediction Model J. Karam, H. Noorvand
https://orcid.org/http://orcid.org/0000-0003-4234-4584
Generally, asphalt concrete experiences permanent deformation due to its exposure to repeated traffic loading during its service life at high temperatures. The objective of this study was to provide an efficient and quick predictive model to easily assess the rutting potential in hot regions. The model was developed using materials properties, traffic, and climatic data gathered from the Long-Term Pavement Performance (LTPP) InfoPave database for 20 different sections in the Dry Freeze and Dry Non-Freeze regions. Performance prediction is one of the widely used methods to assess pavement performance during its service life. It is also used to in pavement management techniques to accommodate the pavement response for specific conditions. Thus, a multiple linear regression model was developed based on data collected from the LTPP database with an R2 of 0.837 and a Se/Sy ratio of 0.47. This model predicts the rutting depth of Hot Mix Asphalt Concrete (HMA) pavements for given structure, climatic conditions, traffic levels and volumetrics properties of asphalt mixtures. The robustness of this model was also compared to two existing models in the literature and was shown to be accurate. In addition, the rutting resistance of various flexible pavement sections at hot and moderate climatic regions within the USA were compared. Based on the collected data, its was found that the maximum temperature had a significant impact on rutting, where higher temperatures increased the rutting development in pavements. On the other hand, some disparities in the measured rutting depth from different states (AZ vs TX) for similar traffic, climate conditions and mixture characteristics were noted. It was explained by the possible improvement in the mix design in certain location, as well as the different aggregates used and construction practices. For those reasons, the overall mechanical response of an HMA pavement is typically governed by the properties of its constituents.
Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
Developing a Rutting Prediction Model J. Karam, H. Noorvand
https://orcid.org/http://orcid.org/0000-0003-4234-4584
Generally, asphalt concrete experiences permanent deformation due to its exposure to repeated traffic loading during its service life at high temperatures. The objective of this study was to provide an efficient and quick predictive model to easily assess the rutting potential in hot regions. The model was developed using materials properties, traffic, and climatic data gathered from the Long-Term Pavement Performance (LTPP) InfoPave database for 20 different sections in the Dry Freeze and Dry Non-Freeze regions. Performance prediction is one of the widely used methods to assess pavement performance during its service life. It is also used to in pavement management techniques to accommodate the pavement response for specific conditions. Thus, a multiple linear regression model was developed based on data collected from the LTPP database with an R2 of 0.837 and a Se/Sy ratio of 0.47. This model predicts the rutting depth of Hot Mix Asphalt Concrete (HMA) pavements for given structure, climatic conditions, traffic levels and volumetrics properties of asphalt mixtures. The robustness of this model was also compared to two existing models in the literature and was shown to be accurate. In addition, the rutting resistance of various flexible pavement sections at hot and moderate climatic regions within the USA were compared. Based on the collected data, its was found that the maximum temperature had a significant impact on rutting, where higher temperatures increased the rutting development in pavements. On the other hand, some disparities in the measured rutting depth from different states (AZ vs TX) for similar traffic, climate conditions and mixture characteristics were noted. It was explained by the possible improvement in the mix design in certain location, as well as the different aggregates used and construction practices. For those reasons, the overall mechanical response of an HMA pavement is typically governed by the properties of its constituents.
Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
Developing a Rutting Prediction Model J. Karam, H. Noorvand
https://orcid.org/http://orcid.org/0000-0003-4234-4584
Generally, asphalt concrete experiences permanent deformation due to its exposure to repeated traffic loading during its service life at high temperatures. The objective of this study was to provide an efficient and quick predictive model to easily assess the rutting potential in hot regions. The model was developed using materials properties, traffic, and climatic data gathered from the Long-Term Pavement Performance (LTPP) InfoPave database for 20 different sections in the Dry Freeze and Dry Non-Freeze regions. Performance prediction is one of the widely used methods to assess pavement performance during its service life. It is also used to in pavement management techniques to accommodate the pavement response for specific conditions. Thus, a multiple linear regression model was developed based on data collected from the LTPP database with an R2 of 0.837 and a Se/Sy ratio of 0.47. This model predicts the rutting depth of Hot Mix Asphalt Concrete (HMA) pavements for given structure, climatic conditions, traffic levels and volumetrics properties of asphalt mixtures. The robustness of this model was also compared to two existing models in the literature and was shown to be accurate. In addition, the rutting resistance of various flexible pavement sections at hot and moderate climatic regions within the USA were compared. Based on the collected data, its was found that the maximum temperature had a significant impact on rutting, where higher temperatures increased the rutting development in pavements. On the other hand, some disparities in the measured rutting depth from different states (AZ vs TX) for similar traffic, climate conditions and mixture characteristics were noted. It was explained by the possible improvement in the mix design in certain location, as well as the different aggregates used and construction practices. For those reasons, the overall mechanical response of an HMA pavement is typically governed by the properties of its constituents.
Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
Developing a Rutting Prediction Model J. Karam, H. Noorvand
Int. J. Pavement Res. Technol.
Karam, Jolina (author) / Noorvand, Hossein (author)
International Journal of Pavement Research and Technology ; 18 ; 234-250
2025-01-01
17 pages
Article (Journal)
Electronic Resource
English
Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
| Springer Verlag | 2025
Correction to: Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
| Springer Verlag | 2025
Correction to: Developing a Rutting Prediction Model for HMA Pavements Using the LTPP Database
| Springer Verlag | 2025