Modeling of Restriping of Waterborne Paints Using Transverse Test Deck Data in Hot and Humid Climate
| Autor: | Elise Mansour, Momen R. Mousa, Marwa Hassan |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Transportation Research Record: Journal of the Transportation Research Board. :036119812311536 |
| ISSN: | 2169-4052 0361-1981 |
| Popis: | The National Transportation Product Evaluation Program (NTPEP) database is a promising tool for U.S. state agencies to evaluate the performance of waterborne paint pavement markings. Out of the total 50 U.S. states, 29 states (57%) utilize the NTPEP data to assess the performance of waterborne paints to be included in the approved materials list. Yet, this dataset is based on transverse retroreflectivity (RL) measurements, which are significantly different from the longitudinal RL measurements in real-world conditions. As such, the key objective of this study was to develop a methodology that converts the transverse RL measurements of waterborne paints to the corresponding longitudinal measurements in hot and humid climate. This approach could be used by transportation agencies to predict the service life of their waterborne paints and make reliable restriping decisions. To achieve this objective, three road sections were selected in Louisiana, U.S., and four different waterborne paints were installed in the transverse and longitudinal directions. These road sections consisted of seven subsections with varying traffic levels and pavement surface types. The data collected included durability readings and longitudinal and transverse RL measurements at five time periods between October 2020 and April 2022. Based on the collected data, two non-linear regression models (for asphalt and concrete surfaces) were developed, with reasonable accuracy, to predict the longitudinal RL of waterborne paints based on the corresponding transverse RL. The predicted longitudinal RL could then be used to determine the expected service life of waterborne paints and make reliable restriping decisions. |
| Databáze: | OpenAIRE |
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