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Prediction of Pavement Surface Temperature Using Meteorological Data for Optimal Winter Operations in Parking Lots
Pavement surface temperature is an essential requirement for the winter maintenance decision-making processes when determining suitable deicers and optimal application rates for transportation facilities such as parking lots. Currently, there are very few services/methods available to directly measure the pavement surface temperature. One method, the Road Weather Information System (RWIS), has less utility for parking lot and sidewalk maintenance purposes due to the operational constraints and high cost of using the RWIS service. This paper presents the results of a two-year field study focused on developing parametric and non-parametric models to forecast pavement surface temperature in parking lots based on a rigorous investigation of its correlation with common meteorological variables. The models were developed using available metrological data alongside measured pavement temperatures obtained through field observations. This study also evaluates the effects of different types of pavement (asphalt, interlocking bricks, and portland cement concrete) on pavement surface temperature. Evaluation results show that the developed models are able to predict pavement surface temperatures in different winter weather conditions with acceptable accuracy.
Prediction of Pavement Surface Temperature Using Meteorological Data for Optimal Winter Operations in Parking Lots
Pavement surface temperature is an essential requirement for the winter maintenance decision-making processes when determining suitable deicers and optimal application rates for transportation facilities such as parking lots. Currently, there are very few services/methods available to directly measure the pavement surface temperature. One method, the Road Weather Information System (RWIS), has less utility for parking lot and sidewalk maintenance purposes due to the operational constraints and high cost of using the RWIS service. This paper presents the results of a two-year field study focused on developing parametric and non-parametric models to forecast pavement surface temperature in parking lots based on a rigorous investigation of its correlation with common meteorological variables. The models were developed using available metrological data alongside measured pavement temperatures obtained through field observations. This study also evaluates the effects of different types of pavement (asphalt, interlocking bricks, and portland cement concrete) on pavement surface temperature. Evaluation results show that the developed models are able to predict pavement surface temperatures in different winter weather conditions with acceptable accuracy.
Prediction of Pavement Surface Temperature Using Meteorological Data for Optimal Winter Operations in Parking Lots
Hosseini, Faranak (author) / Hossain, S. M. Kamal (author) / Fu, Liping (author) / Johnson, Marc (author) / Fei, Yuheng (author)
16th International Conference on Cold Regions Engineering ; 2015 ; Salt Lake City, Utah
Cold Regions Engineering 2015 ; 440-451
2015-07-17
Conference paper
Electronic Resource
English
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