Modeling of Asphalt Pavement Surface Temperature for Prevention of Icing on the Surface

Yıl 2024, Cilt: 35 Sayı: 2, 1 - 21, 01.03.2024

Hüseyin Akbulut , Lale Atılgan Gevrek , Murat Ay

https://doi.org/10.18400/tjce.1211542

Cited By: 1

Öz

Hydronic heating systems are emerging as one of the best methods, which are environmentally friendly, clean, and sustainable modern ice prevention methods, an alternative to traditional ice precautions in the pavements. In this present study, temperatures were measured on asphalt samples prepared using the hydronic heating system when the air temperature in situ fell below 0 °C. T(minute), the temperature of influent (°C), air temperature (°C), temperature of effluent (°C) and pavement mean temperature (°C) were measured for four different asphalt samples. The results of the measurements were then modeled separately for four samples (345×4=1380 data) by using multiple linear regression (MLR), multi-layer perceptron (MLP), and radial basis neural network (RBNN). The results were discussed as tables and graphs. The performances of the models were evaluated using the root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R2). According to the results, the RBNN models of four inputs had the best performance for each sample. The RBNN (4,0.6,9) model, which refers to 4-inputs, spread coefficient of 0.6 and hidden nodes of 9, of sample-3 with RMSE=0.76 °C and MAE=0.63 °C and R2=0.91 had the best performance among all models. In addition, it is thought that the models having low errors in this concept can be evaluated for early warning systems for the ice condition of the roads.

Anahtar Kelimeler

Ice prevention, modeling of pavement temperature, traffic safety

Destekleyen Kurum

Afyon Kocatepe University

Proje Numarası

Afyon Kocatepe University, 18.FENBİL.41.

Teşekkür

We would like to thank Afyon Kocatepe University, Scientific Research Projects Coordination Unit for supporting this study with the project number 18.FENBİL.41.

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