本文讨论了影响沥青路面车辙变形的主要因素。提出基于轮辙试验的车辙预估模型新框架。用沥青混合料动稳定度 DS_5作为沥青混合料自身抵抗车辙变形的综合阻抗参数;利用沥青混合料横向流动动力参数 K 积分和累积荷载时间概念,由轮辙试验...本文讨论了影响沥青路面车辙变形的主要因素。提出基于轮辙试验的车辙预估模型新框架。用沥青混合料动稳定度 DS_5作为沥青混合料自身抵抗车辙变形的综合阻抗参数;利用沥青混合料横向流动动力参数 K 积分和累积荷载时间概念,由轮辙试验变形规律建立车辙预估模型。展开更多
The rutting simulation method considering temperature variance and traffic time distribution is developed through ABAQUS software. The short-term behavior of pavement rut under the effects of temperature and traffic l...The rutting simulation method considering temperature variance and traffic time distribution is developed through ABAQUS software. The short-term behavior of pavement rut under the effects of temperature and traffic loading is addressed. Then sensitivity analysis on the factors of temperature and traffic loading is conducted and a short-term rutting prediction model is developed. The results show that under the same conditions of temperature and the number of load repetitions, rut increases sharply with the contact pressure in a linear manner, while as for the heavy load situation, the increases likely to be more nonlinear and faster; the significant factors affecting rutting include daily maximum air temperature, daily solar radiation volume, daily minimum air temperature, tire-pavement contact pressure and the number of load repetitions. Finally, a short-term rutting prediction model reflecting the effects of air temperature and traffic loading is developed, and it can be used for prediction and pre-waming for pavement rut prevention.展开更多
基金The National High Technology Research and Development Program of China (863 Program)(No.2006AA11Z110)
文摘The rutting simulation method considering temperature variance and traffic time distribution is developed through ABAQUS software. The short-term behavior of pavement rut under the effects of temperature and traffic loading is addressed. Then sensitivity analysis on the factors of temperature and traffic loading is conducted and a short-term rutting prediction model is developed. The results show that under the same conditions of temperature and the number of load repetitions, rut increases sharply with the contact pressure in a linear manner, while as for the heavy load situation, the increases likely to be more nonlinear and faster; the significant factors affecting rutting include daily maximum air temperature, daily solar radiation volume, daily minimum air temperature, tire-pavement contact pressure and the number of load repetitions. Finally, a short-term rutting prediction model reflecting the effects of air temperature and traffic loading is developed, and it can be used for prediction and pre-waming for pavement rut prevention.
