Analysis of critical factors to asphalt overlay performance using gradient boosted models. (30th November 2020)
- Record Type:
- Journal Article
- Title:
- Analysis of critical factors to asphalt overlay performance using gradient boosted models. (30th November 2020)
- Main Title:
- Analysis of critical factors to asphalt overlay performance using gradient boosted models
- Authors:
- Zhang, Miaomiao
Gong, Hongren
Jia, Xiaoyang
Xiao, Rui
Jiang, Xi
Ma, Yuetan
Huang, Baoshan - Abstract:
- Highlights: Introducing gradient boosted models to predict pavement performance. Identifying the impact of pre-overlay conditions on overlay performance. Identifying variables critical to the evolution of overlay performance. Pre-overlay rutting and transverse cracking were crucial to overlay performance. Abstract: Traditional pavement performance predictions based on empirical equations typically utilize only a limited number of parameters to form relatively simple models, thus fail to generate predictions of satisfactory accuracy. With the ever-increasing size of pavement data, model-free methods such as analytical learning algorithms have become promising alternatives. Therefore, to improve the accuracy of pavement performance prediction and take advantage of the existing large dataset, this study introduced an analytical approach, the gradient tree boosting model (GTBM), to predict asphalt overlay performance and identify key factors affecting it. Five indicators were selected to represent the overlay performance, including roughness (in international roughness index, IRI), rutting, fatigue cracking, transverse cracking, and longitudinal cracking. All data were collected from the Specific Pavement Studies 5 (SPS-5) in the Long-Term Pavement Performance (LTPP) program. The results showed that pre-overlay rutting and transverse cracking were crucial to the development of overlay performance, thus pretreatment of repairing existing rutting and transverse cracking on the oldHighlights: Introducing gradient boosted models to predict pavement performance. Identifying the impact of pre-overlay conditions on overlay performance. Identifying variables critical to the evolution of overlay performance. Pre-overlay rutting and transverse cracking were crucial to overlay performance. Abstract: Traditional pavement performance predictions based on empirical equations typically utilize only a limited number of parameters to form relatively simple models, thus fail to generate predictions of satisfactory accuracy. With the ever-increasing size of pavement data, model-free methods such as analytical learning algorithms have become promising alternatives. Therefore, to improve the accuracy of pavement performance prediction and take advantage of the existing large dataset, this study introduced an analytical approach, the gradient tree boosting model (GTBM), to predict asphalt overlay performance and identify key factors affecting it. Five indicators were selected to represent the overlay performance, including roughness (in international roughness index, IRI), rutting, fatigue cracking, transverse cracking, and longitudinal cracking. All data were collected from the Specific Pavement Studies 5 (SPS-5) in the Long-Term Pavement Performance (LTPP) program. The results showed that pre-overlay rutting and transverse cracking were crucial to the development of overlay performance, thus pretreatment of repairing existing rutting and transverse cracking on the old pavement is essential to prolong the service life of asphalt overlay. The initial value of overlay IRI was the most critical factor for the IRI prediction. Besides, overlay roughness was found to be strongly related to the asphalt content and gradation of hot mix asphalt (HMA); fatigue cracking exhibited a close relationship with the thickness of underlying pavements and asphalt viscosity; transverse cracking was strongly associated with the air voids of HMA; non-wheel path longitudinal cracking was relevant to the asphalt content and gradation of HMA. … (more)
- Is Part Of:
- Construction & building materials. Volume 262(2021)
- Journal:
- Construction & building materials
- Issue:
- Volume 262(2021)
- Issue Display:
- Volume 262, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 262
- Issue:
- 2021
- Issue Sort Value:
- 2021-0262-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11-30
- Subjects:
- Asphalt overlay -- Pavement performance -- Gradient tree boosting model -- Relative importance -- LTPP
Building materials -- Periodicals
624.18 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09500618 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.conbuildmat.2020.120083 ↗
- Languages:
- English
- ISSNs:
- 0950-0618
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3420.950900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14738.xml