Multi-factor prediction of permanent deformation of asphalt pavement at continuous variable temperature
1. Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang′an University, Xi′an, Shaanxi 710064, China; 2. Shandong Provincial Communications Planning and Design Institute Group Co., Ltd., Jinan, Shandong 250101, China; 2. Shaanxi Transportation Holding Group Co., Ltd., Xi′an, Shaanxi 710065, China
Abstract： The effects of ambient temperature, driving load and driving speed on the permanent deformation of asphalt pavement were explored. The grey correlation method was used to determine the significance level of the influence of multiple factors of continuous temperature change conditions, pavement material deformation characteristics and construction quality on rutting deformation. According to the principle of equivalent rutting deformation, the equivalent temperature numerical simulation analysis was carried out, and the rutting deformationtemperature relationship model was obtained to determine the equivalent temperature of rutting deformation in different months. A finite element analysis method of longterm permanent deformation of asphalt pavement was established based on ABAQUS, which was used to analyze the variation law of actual rutting deformation of asphalt pavement with service time. The results show that the environmental temperature, the driving load and the driving speed all have great influence on the rutting deformation of asphalt pavement, and the decreasing influence sequence is the environmental temperature, the driving load and the driving speed. The numerical simulation analysis of equivalent temperature shows that the monthly equivalent temperature of rutting can effectively characterize the rutting deformation of the pavement. The established prediction model can effectively predict the permanent deformation of the asphalt pavement, which can provide reference for controlling the construction quality of the asphalt pavement and guiding the later maintenance of the pavement.
NAHI M H, KAMARUDDIN I, NAPIAH M. Rutting prediction in asphalt pavement based on viscoelastic theory[J]. MATEC Web of Conferences, doi: 10.1051/matecconf/20167801035.
LIU X D, FAN Z Y. A finite element prediction model for road rutting based on creep parameters[J]. Journal of China and Foreign Highway, 2015, 35(1): 43-45. (in Chinese)
［3］
王海燕,纪小平,王延海, 等.车辙预估模型研究[J].公路,2015,60(2):40-45.
WANG H Y, JI X P, WANG Y H, et al. Ｓｔｕｄｙ ｏｆ ｒｕｔｔｉｎｇ ｐｒｅｄｉｃｔｉｏｎ ｍｏｄｅl[J]. Highway, 2015, 60(2): 40-45. (in Chinese)
GU X Y, YUAN Q Q, NI F J. Analysis of factors on asphalt pavement rut development based on measured load and temperature gradient [J]. China Journal of Highway and Transport, 2012, 25(6): 30-36. (in Chinese)
YANG C S, ZHANG X H, ZHANG S L, et al. Numerical simulation of temperature field of high temperature mixing valve based on multiphysical field coupling [J]. Fluid Machinery, 2021, 49(5): 54-60. (in Chinese)
LI X G, LIANG W X, LU X. Research on expressway overload coefficient based on axle load spectrum[J]. Journal of China and Foreign Highway, 2013, 33(3): 324-326. (in Chinese)
［7］
张兰峰. 基于移动荷载和连续变温条件下沥青路面结构力学响应研究[D]. 西安：长安大学,2018.
［8］
LEWANDOWSKI M, GAJEWSKI M, JEMIOLO S. The material anisotropy influence on modelling of rutting test with application of linear viscoelasticity constitutive equations[J]. Procedia Engineering, 2014, 91:93-98.
ZHANG K, ZHANG Z Q, LUO Y F. Evaluation standard for antirutting performance of asphalt pavement based on cylindrical core sample [J]. Bulletin of the Chinese Ceramic Society, 2018, 37(6): 1951-1959. (in Chinese)
[10]
ARABANI M, JAMSHIDI R, SADEGHNEJAD M. Using of 2D finite element modeling to predict the glasphalt mixture rutting behavior[J]. Construction and Building Materials, 2014, 68:183-191.
