多物理
沥青
老化
材料科学
环境科学
有限元法
工程类
复合材料
结构工程
遗传学
生物
作者
Eman L. Omairey,Fan Gu,Yuqing Zhang
标识
DOI:10.1016/j.jclepro.2020.124401
摘要
Long-term oxidative ageing occurs in asphalt pavements when they are exposed to the ambient environment for extended periods. This ageing phenomenon is dependent on multiple physical fields, including heat transfer, oxygen diffusion from air into interconnected air voids of asphalt pavement, oxygen diffusion from air void channels to asphalt mastic inside, and growth of oxidation products in bitumen. Most existing oxidative ageing models were established via coupling of limited physical fields. However, to accurately determine the oxidative ageing effect on pavement performance, there is a need to develop a multiphysics model that integrates all ageing-related physical fields comprehensively. The challenge lies in that the ageing-related physics are circularly dependent, time-dependent and highly nonlinear. This study developed a multiphysics and time-dependent finite element model that successfully addressed the issues of high nonlinearity and circular dependency of oxidative ageing in the asphalt pavements. Specifically, a differential equation-based approach was employed to efficiently couple the multiple physical fields into one integrated model. The multiphysics framework included a pavement temperature prediction model and an integrated ageing model. The model involved a variety of inputs such as site-specific hourly climate data, parameters for oxidation kinetics of bituminous binder, volumetric properties of asphalt mixture, thermal and diffusive properties of pavement materials, and pavement structure. The pavement temperature model was validated using the pavement temperature profiles for different climate regions in the Long-Term Pavement Performance (LTPP) database. The integrated ageing model was validated using the Fourier-transform infrared spectroscopy (FTIR) data of field-aged asphalt cores in the literature. Results showed that the model can accurately predict the change in pavement temperature profile on an hourly basis and reliably predict the degree of oxidative ageing across pavement depth for different climate zones.
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