Modeling the surface stored thermal energy in asphalt concrete pavements

Regression analysis is used to develop models for minimal daily pavement surface temperature, using minimal daily air temperature, day of the year, wind speed and solar radiation as predictors, based on data from Awbari, Lybia,. Results were compared with existing SHRP and LTPP models. This paper al...

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Bibliographic Details
Published in:Thermal science 2016, Vol.20 (suppl. 2), p.603-610
Main Authors: Matic, Bojan, Salem, Hasan, Radonjanin, Vlastimir, Radovic, Nebojsa, Sremac, Sinisa
Format: Article
Language:English
Subjects:
Air temperature
Asphalt
Concrete pavements
Neural networks
Regression analysis
Solar radiation
Thermal energy
Wind speed
Online Access:Get full text
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Summary:Regression analysis is used to develop models for minimal daily pavement surface temperature, using minimal daily air temperature, day of the year, wind speed and solar radiation as predictors, based on data from Awbari, Lybia,. Results were compared with existing SHRP and LTPP models. This paper also presents the models to predict surface pavement temperature depending on the days of the year using neural networks. Four annual periods are defined and new models are formulated for each period. Models using neural networks are formed on the basis of data gathered on the territory of the Republic of Serbia and are valid for that territory.
ISSN:0354-9836
2334-7163
DOI:10.2298/TSCI150930042M