Published: 2024-12-17

Optimisation of BELLS3 model coefficients to increase the precision of asphalt layer temperature calculations in FWD and TSD measurements

Jacek Sudyka , Tomasz Mechowski , Przemysław Harasim , Mirosław Graczyk , Andrzej Matysek

Abstract

The article discusses the optimisation process of the BELLS3 model for predicting the temperature of asphalt layers, especially in deflection measurements on Polish roads. The BELLS3 model, based on data from the Long-Term Pavement Performance programme, is a popular tool for quick and non-contact temperature estimation of asphalt layers at various depths. However, its accuracy may be limited in the context of local climatic conditions, which differ from those included in the original model. In this paper, a verification analysis was carried out through testing the model on FWD measurements data, and then the model was optimised using the least squares method (LSM). This approach yielded a small improvement in accuracy (only 1%) while reducing the error to 2.12°C. Therefore, it was decided to extend the analysis by using a machine learning method (MARS) to obtain the explicit form of the model. The solution improved the accuracy by 6%, at the same time reducing the error to 1.84°C. Based on this, further research was suggested on hybrid and AI-based models that could improve the efficiency of asphalt layer temperature forecasting under local climatic conditions.

Keywords:

BELLS3, deflections, FWD, pavement, temperature, TSD, validation

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Sudyka, J., Mechowski, T., Harasim, P., Graczyk, M., & Matysek, A. (2024). Optimisation of BELLS3 model coefficients to increase the precision of asphalt layer temperature calculations in FWD and TSD measurements. Roads and Bridges – Drogi I Mosty, 23(4), 437–456. https://doi.org/10.7409/rabdim.024.021

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