A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Prediction of Rutting Depth Using Random Forest Methods in Full-Depth Reclamation Asphalt Pavements
https://orcid.org/http://orcid.org/0000-0003-0078-1647
https://orcid.org/http://orcid.org/0000-0002-4334-4474
Traditional pavement design relies on computational deterioration models that were trained using relatively small datasets and solid mechanic theory. This paper analyzes full-depth reclamation (FDR), a pavement recycling rehabilitation alternative that is not modeled effectively in current design models. A random forest algorithm is calibrated based on empirical data collected from 10 FDR sites in Colorado. The resulting model yields significant improvements compared to the mechanistic-empirical model currently used in pavement design, with a reduction in RMSE of 86.7%. The study found that precipitation and freezing index have the greatest impact on rutting depth at the end of the pavement design life, with changes in traffic having a significantly lower impact on rutting. This study provides a framework for utilizing large amounts of condition, climatic, and traffic data to model pavement deterioration.
Prediction of Rutting Depth Using Random Forest Methods in Full-Depth Reclamation Asphalt Pavements
https://orcid.org/http://orcid.org/0000-0003-0078-1647
https://orcid.org/http://orcid.org/0000-0002-4334-4474
Traditional pavement design relies on computational deterioration models that were trained using relatively small datasets and solid mechanic theory. This paper analyzes full-depth reclamation (FDR), a pavement recycling rehabilitation alternative that is not modeled effectively in current design models. A random forest algorithm is calibrated based on empirical data collected from 10 FDR sites in Colorado. The resulting model yields significant improvements compared to the mechanistic-empirical model currently used in pavement design, with a reduction in RMSE of 86.7%. The study found that precipitation and freezing index have the greatest impact on rutting depth at the end of the pavement design life, with changes in traffic having a significantly lower impact on rutting. This study provides a framework for utilizing large amounts of condition, climatic, and traffic data to model pavement deterioration.
Prediction of Rutting Depth Using Random Forest Methods in Full-Depth Reclamation Asphalt Pavements
https://orcid.org/http://orcid.org/0000-0003-0078-1647
https://orcid.org/http://orcid.org/0000-0002-4334-4474
Traditional pavement design relies on computational deterioration models that were trained using relatively small datasets and solid mechanic theory. This paper analyzes full-depth reclamation (FDR), a pavement recycling rehabilitation alternative that is not modeled effectively in current design models. A random forest algorithm is calibrated based on empirical data collected from 10 FDR sites in Colorado. The resulting model yields significant improvements compared to the mechanistic-empirical model currently used in pavement design, with a reduction in RMSE of 86.7%. The study found that precipitation and freezing index have the greatest impact on rutting depth at the end of the pavement design life, with changes in traffic having a significantly lower impact on rutting. This study provides a framework for utilizing large amounts of condition, climatic, and traffic data to model pavement deterioration.
Prediction of Rutting Depth Using Random Forest Methods in Full-Depth Reclamation Asphalt Pavements
Lecture Notes in Civil Engineering
Desjardins, Serge (editor) / Poitras, Gérard J. (editor) / Nik-Bakht, Mazdak (editor) / Evers, Eli (author) / Shrestha, Atithi (author) / Garcia, Erick (author) / Cho, Haechad (author) / Bashar, Mohammad Z. (author) / Torres-Machi, Cristina (author) / Choi, Kunhee (author)
Canadian Society of Civil Engineering Annual Conference ; 2023 ; Moncton, NB, Canada
2024-09-18
13 pages
Article/Chapter (Book)
Electronic Resource
English
Lime-Flyash Stabilization of Asphalt Pavements Using Full-Depth Reclamation
| British Library Conference Proceedings | 2010
Full Depth Reclamation of Asphalt Pavements Using Coal Combustion Byproducts
| British Library Conference Proceedings | 2012
Full Depth Reclamation of Asphalt Pavements Using Class F Fly Ash
| British Library Conference Proceedings | 2007
Rutting analysis of full depth asphalt mix
| TIBKAT | 1986