Cold in-place recycling pavement rutting prediction model using grey modeling method

Abstract

The rut depth prediction model (RDPM), based on grey modeling method, can be an efficient and accurate model to predict rut depth. The concept of grey modeling method is introduced and the model prediction equation is derived. The RDPM was developed using rut depth data from wet and dry test conditions by asphalt pavement analyzer (APA). All cold in-place recycling (CIR) test samples consisted of reclaimed asphalt pavement (RAP) mixed with asphalt emulsion and additives were fabricated using a Superpave gyratory compactor. The parameters of RDPM are determined from two of the compacted samples and the model is verified by one of the samples of the same asphalt emulsion contents and test condition. The regression analysis shows that the RDPM is useful for making rut depth predictions, regardless of dry or wet test conditions. Thus, the RDPM can be used to estimate anticipated rut depths if the loading cycles are known.