TY - JOUR
T1 - Investigation and modelling of asphalt pavement performance in cold regions
AU - Zeiada, Waleed
AU - Hamad, Khaled
AU - Omar, Maher
AU - Underwood, B. Shane
AU - Khalil, Mohamad Ali
AU - Karzad, Abdul Saboor
N1 - Publisher Copyright:
© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/8/3
Y1 - 2019/8/3
N2 - The performance of asphalt pavement is highly affected by climate factors, such as temperature and precipitation. Different temperature and moisture conditions change the paving material properties, which consequently influence pavement performance. Considerable research has been conducted to study the effect of climate factors on pavement performance; however, there are no focused studies that have investigated the performance of asphalt pavements in cold regions. In this research, the effect of different design factors on asphalt pavement performance in cold regions is investigated utilising data extracted from the Long-Term Pavement Performance database. Only control sections with no historical maintenance or rehabilitation records were considered. The International Roughness Index (IRI) was adopted as the pavement performance measure. The IRI value is expected to increase gradually over time due to pavement deterioration. Initial screening of the data showed that most of the pavement sections experienced remarkable IRI increase followed by an unexpected decrease. An in-depth investigation revealed that frost heave was the main reason of this unexpected IRI trend as it was correlated in most of the cases to sudden monthly freezing index increases, especially for sections with no subsurface drainage and less layers thicknesses. An Artificial Neural Network with a Forward Sequential Feature Selection algorithm and regression analysis were employed to model pavement performance in cold regions and determine the most significant design factors prevailing in cold climate conditions. Moreover, a sensitivity analysis was performed to investigate the interrelation between the considered features and the IRI. As a result, several climate-related factors were found to have a significant impact on the performance of asphalt pavements in cold regions such as average temperature, freezing index, freeze/thaw, wind velocity and relative humidity.
AB - The performance of asphalt pavement is highly affected by climate factors, such as temperature and precipitation. Different temperature and moisture conditions change the paving material properties, which consequently influence pavement performance. Considerable research has been conducted to study the effect of climate factors on pavement performance; however, there are no focused studies that have investigated the performance of asphalt pavements in cold regions. In this research, the effect of different design factors on asphalt pavement performance in cold regions is investigated utilising data extracted from the Long-Term Pavement Performance database. Only control sections with no historical maintenance or rehabilitation records were considered. The International Roughness Index (IRI) was adopted as the pavement performance measure. The IRI value is expected to increase gradually over time due to pavement deterioration. Initial screening of the data showed that most of the pavement sections experienced remarkable IRI increase followed by an unexpected decrease. An in-depth investigation revealed that frost heave was the main reason of this unexpected IRI trend as it was correlated in most of the cases to sudden monthly freezing index increases, especially for sections with no subsurface drainage and less layers thicknesses. An Artificial Neural Network with a Forward Sequential Feature Selection algorithm and regression analysis were employed to model pavement performance in cold regions and determine the most significant design factors prevailing in cold climate conditions. Moreover, a sensitivity analysis was performed to investigate the interrelation between the considered features and the IRI. As a result, several climate-related factors were found to have a significant impact on the performance of asphalt pavements in cold regions such as average temperature, freezing index, freeze/thaw, wind velocity and relative humidity.
KW - LTPP
KW - Pavement performance
KW - artificial neural network
KW - cold regions
KW - frost heave
KW - sequential feature selection
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U2 - 10.1080/10298436.2017.1373391
DO - 10.1080/10298436.2017.1373391
M3 - Article
AN - SCOPUS:85029411739
SN - 1029-8436
VL - 20
SP - 986
EP - 997
JO - International Journal of Pavement Engineering
JF - International Journal of Pavement Engineering
IS - 8
ER -