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Modeling the surface stored thermal energy in asphalt concrete pavements

By Matić Bojan J., Salem Hasan Awadat, Radonjanin Vlastimir S., Radović Nebojša M. and Sremac Siniša R.

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

Topics: pavement, temperature, model, predicting, ANN, regression analysis, thermal energy, Mechanical engineering and machinery, TJ1-1570
Publisher: VINCA Institute of Nuclear Sciences
Year: 2016
DOI identifier: 10.2298/TSCI150930042M
OAI identifier: oai:doaj.org/article:fb9e6b327e934d64bd959f14b4928294
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