Influence of Fine Aggregate Particle Size on Viscoelastic Parameters of Asphalt Mortar by Gray Entropy Method

Abstract

Abstract: Uni-axial compression creep test is carried out on asphalt mortar of different fine aggregate compositions, and the results of creep test are fitted by Burgers mode. Then the influence degree of fine aggregate particle size on viscoelastic parametersis analyzed by the gray entropy method,in order to make apreliminary study of the viscoelastic property of asphalt mortar. The results show that:the aggregates ranging from 1.18mm to 2.36mm exert significant influence on viscoelastic parameters E1 , E2 and η2 ;the influence of aggregates smaller than 0.075mm on four viscoelastic parameters takes the second place; the aggregate ranging from 2.36mm to 4.75mm exerts significant influence on viscoelastic parametersη1 .

Key words: road engineering, asphalt mortar, fine aggregate, creep test, Burgers model, influence degree, gray entropy method

摘要： 对不同细集料粒径组成的沥青砂浆进行单轴压缩蠕变试验,用Burgers模型拟合蠕变试验结果,并通过灰熵法分析了细集料粒径对黏弹性参数的影响程度,以研究沥青砂浆的黏弹性特性。研究结果表明:1.18～2.36mm 档集料对黏弹性参数E1、E2、η2均产生显著的影响;小于0.075mm档集料对4个黏弹性参数的影响程度都居于其次;2.36～4.75mm档集料对参数η1的影响程度显著。

关键词: 道路工程, 沥青砂浆, 细集料, 蠕变试验, Burgers模型, 影响程度, 灰熵法

CLC Number:

U414

YING Rong-hua,HOU Zhao-guang,PANG Hai-feng. Influence of Fine Aggregate Particle Size on Viscoelastic Parameters of Asphalt Mortar by Gray Entropy Method[J]. Journal of Chongqing Jiaotong University(Natural Science), 2010, 29(3): 398-402.

应荣华,侯昭光,庞海峰. 细集料粒径对沥青砂浆黏弹性参数影响程度的灰熵分析[J]. 重庆交通大学学报（自然科学版）, 2010, 29(3): 398-402.

[1]	YE Juntao, ZHANG Dawei. Estimation Method of Mean Texture Depth for Cement Concrete Pavements [J]. Journal of Chongqing Jiaotong University(Natural Science), 2026, 45(1): 7-14.
[2]	YUE Hongzhi1,2, CHEN Yingjiao3, ZHAO Lin1,2, ZHOU Haifang3, LYU Quan4. Pavement Performance of Chemically Activated Terminal Blend Rubber Powder Modified Asphalt Mixtures [J]. Journal of Chongqing Jiaotong University(Natural Science), 2025, 44(7): 59-66.
[3]	XU Xinquan1, HU Yuanjiao2, WENG Yuhan3, HE Weijie1. Road surface texture is a key factor affecting the skid resistance performance. To further study its influence mechanism and to solve the problem of limited accuracy of traditional prediction methods under multi-feature data conditions, a pavement skid resistance performance assessment model based on the fusion of Bayesian optimization algorithm (BOA) and extreme gradient boosting (XGBoost) was proposed. Firstly, specimens phalt mixtures of different gradation types were prepared. Friction data and 3D texture data of the specimen surface were respectively obtained by using a pendulum friction meter and a 3D laser scanning device. Secondly, the height, the wavelength and shape parameters were extracted to describe the texture structure, and the texture feature importance analysis was carried out to clarify the factors that significantly affected the skid resistance. Then, the optimal key parameters were improved by introducing of the model BOA-XGBoost and the prediction model of skid resistance performance was established. The research results show that compared with the comparative models, the proposed model has higher accuracy, with a correlation coefficient R2 of 0.890 6, which is 25.2%, 13.0%, and 15.1% higher than those of the comparative models, respectively. The proposed model can effectively correlate texture features with pavement skid resistance performance. [J]. Journal of Chongqing Jiaotong University(Natural Science), 2025, 44(6): 35-44.
[4]	WANG Lijun, FANG Qingtian. Microwave Warming Performance of Ferrite-Silicon Carbide Asphalt Mixture [J]. Journal of Chongqing Jiaotong University(Natural Science), 2025, 44(6): 53-63.
[5]	MA Hongyan1, WENG Mingsheng1, HUANG Renjie1, XU Song1, ZHENG Litang2. Shear Strength Characteristics and Prediction Model of Polypropylene Fiber Modified Red Clay under Dry-Wet Cycle [J]. Journal of Chongqing Jiaotong University(Natural Science), 2025, 44(3): 33-39.
[6]	WANG Chao, SUN Yanguang, REN Zhengyang. Fatigue and Fracture Behavior Mechanism of Asphalt Based on Damage Tolerance Design Theory: Feature Discrimination,Mechanistic Criterion and Performance Prediction [J]. Journal of Chongqing Jiaotong University(Natural Science), 2025, 44(1): 8-16.
[7]	WANG Yuanyuan1,LI Renjie2,LIU Yanyan3,ZHANG Hengtong2,LIU Dezheng2. Laser-Constrained Binocular Robust Algorithm for Measuring 3D Texture of Pavement [J]. Journal of Chongqing Jiaotong University(Natural Science), 2024, 43(2): 24-29.
[8]	YANG Bo1,2, ZHOU Bo1, CHENG Yihuan1, ZHANG Meng1, TANG Naipeng1,2. Road Performance of Oyster Shell Powder Asphalt Mortar [J]. Journal of Chongqing Jiaotong University(Natural Science), 2024, 43(1): 26-30.
[9]	BAO Xueying1, ZHAO Jinxia1, BAN Xinlin2,3, XU Jianchao2,3. Risk Factors of Railway Bridge and Tunnel Engineering Technology Interface [J]. Journal of Chongqing Jiaotong University(Natural Science), 2023, 42(9): 18-26.
[10]	LI Zhiyong, ZHU Shangshu. Road Performance of Light-Colored Pavement Materials [J]. Journal of Chongqing Jiaotong University(Natural Science), 2023, 42(2): 37-43.
[11]	CAI Fengjie, FENG Zhengang, YAO Dongdong, CHEN Tingting, WEI Jincheng. Rapid Detection Method of Asphalt Creep Recovery Performance [J]. Journal of Chongqing Jiaotong University(Natural Science), 2023, 42(1): 54-59.
[12]	LI Shanghui1, QUE Yun2, ZHAN Xiaojun2. Experimental Study on Non-equilibrium Flow and Instability Characteristics on Macropores Slope under Rainfall Conditions [J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(12): 104-111.
[13]	GAO Luchao1, CHEN Hede2, HE Zirui3, HUA Xin4, HU Chuankai4. Creep Characteristics of Interactive Marine Terrestrial Deposit Soil Based on Fractal Derivative [J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(12): 120-127.
[14]	YANG Jun1, TANG Shengang1, XU Xinquan1,2. Influence of Fine Aggregate Properties on the Technical Performance of GAC-16 Asphalt Mixture [J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(08): 112-119.
[15]	PENG Bo1, YANG Zhongchang1, REN Ziming2, WU Shiyuan3, DU Bingjie2. Crack Resistance Performance of Cement-Soil Stabilized RAP Mixture Based on Pre-slit Test [J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(05): 92-99.