Using sensing, statistical, and numerical analysis approaches to evaluate the effect of temperature change on the resilient performance of highway pavements

Abstract

The paper is to evaluate the effect of temperature change on the performance (i.e., roughness, mechanical response, etc.) of highway pavement using vehicle-based sensing technology, statistical analysis and numerical analysis. A year-long vibration data and pavement temperature (02/2017–02/2018) were collected on the two test sections along the I-10 corridors in the Phoenix region. Vibration data is processed, analyzed and validated with international roughness index (IRI) data to ensure the sensing results are statistically valid for the performance evaluation. The sensing results show that hot pavement temperatures increase the frequency of pavement distresses. A follow up ANOVA analysis also confirms that the effect of temperature changes on the performance of pavement is significant. A series of numerical analyses using the finite element method were further performed to analyze pavement stresses under the action of traffic loads and thermal expansion/contraction on the two test sections. The numerical analysis results indicate that among the length of experiment, the pavement stresses increased dramatically from May to August meaning that in the summertime (May to August in the Phoenix region) passengers travelling on the I-10 corridors would experience discomfort and bumpy. The paper shows that field vibration data and numerical analyses are in good agreement with the performance evaluation (roughness and mechanical response) of highway pavement and concludes that the effect of temperature change on the performance of pavement in the Phoenix region is significant.