THERMAL SCIENCE

International Scientific Journal

MODELING THE SURFACE STORED THERMAL ENERGY IN ASPHALT CONCRETE PAVEMENTS

ABSTRACT
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. [Projekat Ministarstva nauke Republike Srbije, br. TR 36017]
KEYWORDS
PAPER SUBMITTED: 2015-09-30
PAPER REVISED: 2015-11-18
PAPER ACCEPTED: 2015-12-16
PUBLISHED ONLINE: 2016-02-20
DOI REFERENCE: https://doi.org/10.2298/TSCI150930042M
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2016, VOLUME 20, ISSUE Supplement 2, PAGES [S603 - S610]
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© 2019 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence