摘要
为研究多碎石沥青混凝土(Stone Asphalt Concrete, SAC)的黏弹特性,通过优化关键筛孔设计了3种(Ⅰ型、Ⅱ型、Ⅲ型)SAC沥青混合料,采用单轴压缩动态模量试验,获取了不同温度及加载频率下的动态模量及相位角,基于时温等效原理建立SAC沥青混合料动态模量主曲线,基于Hirsch模型建立了SAC沥青混合料的预测模型并对预测精度进行评价。结果表明:SAC沥青混合料动态模量与温度及加载频率有较强的相关性,SAC沥青混合料动态模量随加载频率增大而增大、随温度升高而减小;增强混合料间的骨架结构有助于提高SAC沥青混合料的动态模量;SAC沥青混合料相位角在低温时(0℃、10℃)随加载频率增大而减小,高温时(40℃)相位角随加载频率增加而增大;基于Hirsch预测模型建立的SAC沥青混合料主曲线预测模型预测精度可达99%,可用于SAC沥青混合料动态模型的预测。
To study the viscoelastic properties of Stone Asphalt Concrete(SAC),three types of SAC asphalt mixtures(Ⅰ,Ⅱ,Ⅲ)are designed by optimizing the key sieve holes.The dynamic modulus and phase angle at various loading frequencies and temperatures are obtained by means of the uniaxial compression dynamic modulus test,and a prediction model based on the time-temperature equivalency principle is established and evaluated for accuracy in predicting the SAC asphalt mixture.The prediction model of SAC asphalt mixtures is established using the Hirsch model,and the predictions accuracy is assessed.The findings indicate that:improving the intermix skeleton structure helps to improve the dynamic modulus of SAC asphalt mixture;at low temperatures(0℃,10℃),the phase angle of SAC asphalt mixture decreases with increasing loading frequency,and at high temperatures(40℃),the phase angle increases with increasing loading frequency;the dynamic modulus of SAC asphalt mixture has a strong correlation with temperature and loading frequency;and the dynamic modulus of SAC asphalt mixture increases with increasing loading frequency.The dynamic model of the SAC asphalt mixture may be predicted using the SAC asphalt mixture main curve prediction model,which is developed based on the Hirsch prediction model and has a prediction accuracy of up to 99%.
作者
姜开明
董鸣亮
冯志鹏
张惠勤
张焕涛
刘洁
JIANG Kai-ming;DONG Ming-liang;FENG Zhi-peng;ZHANG Hui-qin;ZHANG Huan-tao;LIU Jie(Shandong Hi-speed Construction Management Group Co.Ltd.,Jinan 250000,China;Shandong Hi-Speed Wendeng Highway Co.Ltd.,Weihai 264400,China;Shandong Hi-Speed Engineering Test Co.Ltd.Jinan 250002,China)
出处
《公路》
北大核心
2025年第5期43-49,共7页
Highway
基金
山东省重点研发计划项目,项目编号2020CXGC011405。
