Development and verification of rutting prediction model based on variable frequency load test

Abstract

ABSTRACT An innovative rutting test method was developed based on the existing rutting prediction model to improve the rutting prediction model used in the asphalt pavements. The loading mould was improved based on test requirements and equipment characteristics, and small-scale and full-scale variable frequency load rutting tests were conducted. Nonlinear multiple regression analysis was conducted on the test results using numerical analysis software, converting driving speed into loading frequency and incorporating it into the rutting prediction model. This resulted in a permanent deformation prediction model for asphalt mixtures, incorporating factors such as temperature, pressure, loading cycles, loading frequency, and pavement thickness. Fourteen highways were selected as validation sections. The validation results showed that the average error of the prediction model established in this study was 15.48%, compared to 24.42% and 27.94% for the other two models. For different grades of highways, the load frequency parameter can distinguish the rutting conditions under different driving speeds, making the rutting prediction model established in this study more accurate compared to measured values.