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Prediction of depth temperature of asphalt layers in hot climate area

    Nader Solatifar   Affiliation
    ; Mojtaba Abbasghorbani Affiliation
    ; Amir Kavussi Affiliation
    ; Henrikas Sivilevičius Affiliation

Abstract

In determination of flexible pavement layers moduli using Falling Weight Deflectometer (FWD), the pavement depth temperature should be determined and then the moduli should be corrected into a reference temperature. As direct measurement of pavement temperature is time consuming and is difficult to be determined in trafficked roads, some models are developed to predict temperature of asphalt layers through pavement depth, including BELLS model. The objective of this research is to determine correlation between actual measurement and prediction of temperature variations through asphalt layers with applying BELLS model. Ten new and rehabilitated pavement sites were selected in hot climate regions in Khuzestan and Kerman provinces in southern part of Iran. In typical hot summer days, pavement temperatures were measured at half and at one-third of the depth of asphalt layers and FWD testing were performed. Results indicated that a linear regression analysis of BELLS predicted temperatures versus measured values, provides very good correlation with actual field measurements of temperatures through the asphalt layers. Furthermore, predictions were more precise in rehabilitated pavements rather than in newly constructed pavements. Finally, using multi parametric linear fitting analysis, a new model was developed to accurately predict the temperature of asphalt layers in new pavements.

Keyword : asphalt layer temperature, BELLS model, Falling Weight Deflectometer (FWD), hot climate areas

How to Cite
Solatifar, N., Abbasghorbani, M., Kavussi, A., & Sivilevičius, H. (2018). Prediction of depth temperature of asphalt layers in hot climate area. Journal of Civil Engineering and Management, 24(7), 516-525. https://doi.org/10.3846/jcem.2018.6162
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Nov 13, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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