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Corresponding Author

黄优，男，博士，副教授.E-mail：hyzju@csust.edu.cn

Abstract

In order to improve the deformation coordination between the built-in strain sensors and asphalt mixtures,high-modulus fine aggregate asphalt mixture AC- 5 and conventional asphalt surface mixture AC- 13 were used as the base materials,and specimens were molded with built-in resistive strain sensors.Uniaxial compression,uniaxial tension,and four-point bending step-by-step loading tests were carried out in conjunction with digital image correlation (DIC).A finite element model verified by hypothesis testing was established to analyze the influence of high-modulus transition materials on deformation coordination under different working conditions such as burial depth of strain gauge,load size,and load type.The results show that under various types of loads,compared with that of the AC- 13 asphalt mixture,the measured strain data of the sensors in the AC-5 high-modulus asphalt mixture is closer to the measured data of DIC,and the measurement error is smaller and more stable.The specimens will have different measurement deviations when subjected to compression and tension,and the high-modulus asphalt mixture has some improvement in the deviation.In terms of the three influencing factors including burial depth of strain gage,load size,load size,and load type,the AC- 5 high-modulus asphalt mixture has different degrees of improvement on the coordinated deformation performance of the strain gage compared with the AC- 13 asphalt mixture.

Publication Date

4-10-2025

DOI

10.14048/j.issn.1671-2579.2025.02.006

First Page

55

Last Page

64

Submission Date

April 2025

Reference

[1]中国共产党中央委员会,中华人民共和国国务院.交通强国建设纲要 [Z],2019.Central Committee of the Communist Party of China,State Council of the People ’s Republic of China.Outline of building a strong transportation country [Z],2019.
[2]赵鸿铎,朱兴一,涂辉招,等.智能铺面的内涵与架构 [J].同济大学学报 (自然科学版 ),2017,45(8):1131 -1135.ZHAO Hongduo,ZHU Xingyi,TU Huizhao,et al.Concept and framework of smart pavement [J].Journal of Tongji University (Natural Science ),2017,45(8):1131 -1135.
[3]WANG Linbing,王含笑,赵千,等.智能路面发展与展望[J].中国公路学报,2019,32(4):50-72.WANG Linbing,WANG Hanxiao,ZHAO Qian,et al.Development and prospect of intelligent pavement [J].China Journal of Highway and Transport,2019,32(4):50-72.
[4]张金喜,王佩荣,曹丹丹,等.基于行车振动的路面车辙评价方法可行性研究 [J].中外公路,2023,43(4):45-51.ZHANG Jinxi,WANG Peirong,CAO Dandan,et al.Feasibility study of pavement rutting evaluation method based on driving vibration [J].Journal of China & Foreign Highway,2023,43(4):45-51.
[5]黄国卿,严筱,杨永刚,等.智能压实间接指标试验分析与压实度预测 [J].中外公路,2020,40(2):24-28.HUANG Guoqing,YAN Xiao,YANG Yonggang,et al.Intelligent compaction indirect indicators test analysis and compactness prediction [J].Journal of China & Foreign Highway,2020,40(2):24-28.
[6]XUE W J,WANG L B,WANG D,et al.Pavement health monitoring system based on an embedded sensing network[J].Journal of Materials in Civil Engineering,2014,26(10):04014072.
[7]BAYAT A,KNIGHT M.Field evaluation and analysis of flexible pavement structural responses under dynamic loads [J].Road Materials and Pavement Design,2012,13(1):26-37.
[8]KARA DE MAEIJER P,VAN DEN BERGH W,VUYE C.Fiber Bragg grating sensors in three asphalt pavement layers [J].Infrastructures,2018,3(2):16.
[9]LIU W Q,LIU X,WANG Z R,et al.High temperature deformation investigation of asphalt mixture with nanosized volcanic ash fillers using optical fiber sensor [J].Measurement,2019,140:171-181.
[10]李海滨,青维,盛燕萍.基于热电能的传感器在路面中的智能应用 [J].中外公路,2016,36(1):309-311.LI Haibin,QING Wei,SHENG Yanping.Intelligent application of sensor based on thermoelectric energy in pavement [J].Journal of China & Foreign Highway,2016,36(1):309-311.
[11]陈凤晨,谭忆秋,董泽蛟,等.基于光纤光栅技术的沥青路面结构应变场分析 [J].公路交通科技,2008,25(10):9-12,21.CHEN Fengchen,TAN Yiqiu,DONG Zejiao,et al.Research on strain field of asphalt pavement based on FBG sensor technique [J].Journal of Highway and Transportation Research and Development,2008,25(10):9-12,21.
[12]谭忆秋,陈凤晨,董泽蛟,等.基于光纤光栅传感技术的沥青路面永久变形计算方法 [J].大连海事大学学报,2008,34(4):119-122.TAN Yiqiu,CHEN Fengchen,DONG Zejiao,et al.Calculation method of permanent deformation for asphalt pavement based on fiber Bragg grating sensing technology[J].Journal of Dalian Maritime University,2008,34(4):119-122.
[13]管志光,庄传仪,林明星.足尺沥青混凝土路面加速加载动力响应 [J].交通运输工程学报,2012,12(2):24-31.GUAN Zhiguang,ZHUANG Chuanyi,LIN Mingxing.Accelerated loading dynamic response of full-scale asphalt concrete pavement [J].Journal of Traffic and Transportation Engineering,2012,12(2):24-31.
[14]AL-QADI I L,LOULIZI A,ELSEIFI M,et al.The virginia smart road:The impact of pavement instrumentation on understanding pavement performance [J].Asphalt Paving Technology:Association of Asphalt Paving Technologists-Proceedings of the Technical Sessions,2004,73:427-46
[15]刘朝晖,李文博,柳力,等.内置应变传感器与沥青路面结构协同工作性能研究 [J].中国公路学报,2023,36(4):1-14.LIU Zhaohui,LI Wenbo,LIU Li,et al.Research on cooperative performance of built-in strain sensor and asphalt pavement structure [J].China Journal of Highway and Transport,2023,36(4):1-14.
[16]谭忆秋,董泽蛟,田庚亮,等.光纤光栅传感器与沥青混合料协同变形评价方法 [J].土木建筑与环境工程,2009,31(2):100-104.TAN Yiqiu,DONG Zejiao,TIAN Gengliang,et al.Evaluating method of the coordination deformation between asphalt mixture and fiber Bragg grating sensor [J].Journal of Civil,Architectural & Environmental Engineering,2009,31(2):100-104.
[17]赵鸿铎,谷松原,马鲁宽.基于数字图像关联技术的沥青应变计测量准确度比对方法 [J].同济大学学报 (自然科学版 ),2018,46(9):1211 -1217.ZHAO Hongduo,GU Songyuan,MA Lukuan.Measurement accuracy comparison of in situ asphalt pavement strain sensors based on digital image correlation technique [J].Journal of Tongji University (Natural Science ),2018,46(9):1211 -1217.
[18]解建光,王秋桐,刘树龙,等.光纤 Bragg光栅监测沥青混凝土应变试验 [J].长安大学学报 (自然科学版 ),2011,31(3):17-20,50.XIE Jianguang,WANG Qiutong,LIU Shulong,et al.Experimental study on strain monitoring of asphalt concrete using FBG (Fiber Bragg Grating ) [J].Journal of Chang’an University (Natural Science Edition ),2011,31(3):17-20,50.
[19]IMAI M,IGARASHI Y,SHIBATA M,et al.Experimental study on strain and deformation monitoring of asphalt structures using embedded fiber optic sensor [J].Journal of Civil Structural Health Monitoring,2014,4(3):209-220.
[20]LIU Z,GU X Y,WU C Y,et al.Studies on the validity of strain sensors for pavement monitoring:A case study for a fiber Bragg grating sensor and resistive sensor [J].Construction and Building Materials,2022,321:126085.
[21]DONG Z J,MA X Y,GONG X B,et al.Theoretical evaluation of the measurement accuracy of fiber Bragg grating strain sensors within randomly filled asphalt mixtures based on finite element simulation [J].Structural Control and Health Monitoring,2018,25(1):e2057.
[22]刘朝晖,夏红卫,柳力.埋入式传感器与沥青混合料的交互影响研究 [J].长沙理工大学学报 (自然科学版 ),2021,18(1):1-6,39.LIU Zhaohui,XIA Hongwei,LIU Li.Research on the interaction effect of embedded sensor and asphalt mixture[J].Journal of Changsha University of Science & Technology (Natural Science ),2021,18(1):1-6,39.
[23]NEDOMA J,FAJKUS M,MARTINEK R,et al.Analysis of the use of fiber-optic sensors in the road traffic [J].IFAC-PapersOnLine,2018,51(6):420-425.
[24]陶宝祺,王妮.电阻应变式传感器 [M].北京:国防工业出版社,1993.TAO Baoqi,WANG Ni.Straingauge type transducer [M].Beijing:National Defense Industry Press,1993.
[25]交通运输部公路科学研究院.公路工程沥青及沥青混合料试验规程:JTG E 20—2011 [S].北京:人民交通出版社,2011.Research Institute of Highway Ministry of Transport.Standard test methods of bitumen and bituminous mixtures for highway engineering:JTG E 20—2011 [S].Beijing:China Communications Press,2011.
[26]周震宇,曾峰,郝玮,等.高模量沥青混合料马歇尔法配合比设计指标研究 [J].公路,2021,66(7):69-75.ZHOU Zhenyu,ZENG Feng,HAO Wei,et al.Research on the design index of mixing ratio for high-modulus asphalt mixture based on Marshall method [J].Highway,2021,66(7):69-75.
[27]程怀磊,孙立军,郑健龙,等.沥青混合料动态压 -拉双模量及其在路面响应分析中的应用 [J].土木工程学报,2022,55(3):105-116,128.CHENG Huailei,SUN Lijun,ZHENG Jianlong,et al.Dynamic compressive-tensile moduli of asphalt mixture and its applications to pavement response prediction [J].China Civil Engineering Journal,2022,55(3):105-116,128.

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