Investigating resilient modulus characteristics and developing unified prediction model of unbound aggregate base materials recycled from construction and demolition waste

被引:0
|
作者
Xiao, Yuanjie [1 ,2 ]
Kong, Kunfeng [1 ,3 ]
Jiang, Yu [1 ]
Hua, Wenjun [1 ]
Zhu, Hongwei [3 ]
Cai, Degou [3 ]
Liu, Yufei [1 ]
机构
[1] School of Civil Engineering, Central South University, Hunan, Changsha,410075, China
[2] Ministry of Education(MOE) Key Laboratory of Engineering Structures of Heavy-haul Railway, Central South University, Hunan, Changsha,410075, China
[3] Railway Engineering Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing,100081, China
来源
Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering | 2022年 / 41卷 / 11期
基金
中国国家自然科学基金;
关键词
Construction and demolition waste - Index properties - Prediction modelling - Recycled aggregates - Resilient modulus - Road engineering - Soil index property - Soil indexes - Stress levels - Unified prediction model;
D O I
暂无
中图分类号
学科分类号
摘要
Resilient modulus(MR) is an important mechanical performance indicator of unbound granular pavement materials subjected to repeated traffic loads, as well as a key input parameter of mechanistic pavement analysis and design. In order to investigate MR characteristics of unbound aggregate materials(UAMs) recycled from construction & demolition waste(CDW) under different combinations of influencing index properties and stress states, laboratory repeated load triaxial tests were conducted on UAMs recycled from single-source CDW, of which five different gradations, three different moisture content levels, three different compaction levels, and 15 different loading sequences were properly designed. The effects of index properties and stress states on MR were analyzed, and a unified MR prediction model was developed and further validated by using the shift factor and master curve concepts to incorporate multiple influencing factors. The laboratory testing results show that resilient modulus of UAMs recycled from CDW gradually decreased with decreasing degree of compaction or increasing moisture content and increased with increasing relative content of coarse particles. Both deviator stress and confining pressure affected resilient modulus of UAMs with the effect of confining pressure being relatively more significant. The unified MR prediction model developed can consider all the influencing factor while yielding satisfactory accuracy. The findings could provide theoretical basis and lay solid foundation for resource-conserving and value-added engineering applications of UAMs recycled from CDW in unbound granular pavement layers. © 2022 Academia Sinica. All rights reserved.
引用
收藏
页码:2337 / 2352
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