摘要: |
为了提出能够合理评价粗集料形态特征(形状、棱角)的定量指标,采用洛杉矶磨耗仪对475~95mm,95~132mm,132~16mm,16~19mm共4档粗集料分别磨耗0,600,1200次,以改变粗集料的形态特征,然后通过自主研制的粗集料形态特征研究系统(MASCA)测得粗集料轴向系数、凸度、粗糙度、棱角参数、圆度、分形维数共6个定量评价指标值,并运用二元方差法比较它们对颗粒形态变化的敏感性,发现分形维数是能够合理评价粗集料形态特征的最优定量指标.为验证这一结论,利用磨耗得到的不同形态特征的粗集料分别成型AC 16,SAC 16,SMA 16级配类型混合料试件进行车辙试验和贯入剪切试验,验证结果表明分形维数与沥青混合料高温性能之间具有很好的相关性. |
关键词: 沥青混合料 粗集料 形态特征 分形维数 高温性能 |
DOI:103969/jissn1007 9629201503028 |
分类号: |
基金项目:国家自然科学基金资助项目(51178056);交通运输部应用基础研究项目(2013 319 812 010) |
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Research on Quantitative Evaluation of Morphological Characteristic of Coarse Aggregates |
LI Xiaoyan1, BU Yin1, WANG Hainian1, WANG Yanzhe1, YOU Zhanping2
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1.Road Structure and Materials Key Laboratory for Transportation, Chang’an University, Xi’an 710064, China;2.Department of Civil and Environmental Engineering, Michigan Technological University, Houghton 49931, USA
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Abstract: |
To obtain the most reasonable quantitative index of the morphological characteristic of coarse aggregates, Los Angeles (LA) abrasion tester without steel balls was employed to change the shape of aggregate particles with size of 47595mm,95132mm,13216mm,1619mm, respectively. Abrasion cycles were 0, 600,and 1200. Through the self developed morphology analysis system of coarse aggregate (MASCA), the values of 6 quantitative indexes (aspect, convexity ratio, roughness, angularity parameter, roundness, fractal dimension) were calculated. Their sensitivity to the change of particle morphology was compared using the method of binary variance. The results show that fractal dimension is the optimal quantitative index to evaluate the morphological characteristic of coarse aggregates. At last, AC 16, SAC 16, SMA 16 mixture specimens were fabricated with the different morphological characteristics of coarse aggregates obtained by abrasion, respectively. The rutting and penetration shear tests were conducted for validation, and test results indicate that the fractal dimension has a good correlation with high temperature performance of asphalt mixture. |
Key words: asphalt mixture coarse aggregate morphological characteristic fractal dimension high temperature performance |