Zhong Chuheng, Xiao Qipeng, Fan Zuwei, Mao Weiqi, Xing Sijia, Chen Jinhui, Xiao Yuan, Zhou Jinzhi
School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan, 430068, China.
Key Laboratory of Health Intelligent Perception and Ecological Restoration of River and Lake, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China.
Sci Rep. 2025 Feb 18;15(1):5855. doi: 10.1038/s41598-025-89682-x.
To reduce the construction industry's reliance on raw natural resources and alleviate the environmental pressures caused by waste concrete, recycling waste concrete materials as recycled coarse aggregate in the production of new concrete presents a viable solution. This study aims to expand the application of recycled aggregate concrete (RAC) in road and bridge engineering. In this experiment, twelve concrete mixtures were designed to investigate the effects of basalt fiber (BF) and polyacrylonitrile fiber (PANF) on the performance of RAC. Based on the flexural strength test, flexural fatigue tests were conducted at various stress levels. Weibull distribution theory was employed to analyze the fatigue life of fiber-doped RAC. Single logarithmic and double logarithmic fatigue equations were developed to predict the ultimate fatigue strength of the specimens. The test results indicated that BF and PANF significantly enhanced both the flexural strength and fatigue life of RAC, with the most notable improvement observed in the mixture containing 0.1% BF and 0.15% PANF. The Weibull theory effectively analyzes the fatigue life with a good fit, and the double logarithmic fatigue equation yields better predictions than the single logarithmic equation.
为减少建筑行业对天然原材料的依赖,并缓解废弃混凝土造成的环境压力,将废弃混凝土材料作为再生粗骨料用于生产新混凝土是一种可行的解决方案。本研究旨在扩大再生骨料混凝土(RAC)在道路与桥梁工程中的应用。在本试验中,设计了12种混凝土混合料,以研究玄武岩纤维(BF)和聚丙烯腈纤维(PANF)对RAC性能的影响。基于抗弯强度试验,在不同应力水平下进行了弯曲疲劳试验。采用威布尔分布理论分析纤维掺杂RAC的疲劳寿命。建立了单对数和双对数疲劳方程来预测试件的极限疲劳强度。试验结果表明,BF和PANF显著提高了RAC的抗弯强度和疲劳寿命,在含有0.1%BF和0.15%PANF的混合料中改善最为显著。威布尔理论能有效分析疲劳寿命,拟合效果良好,双对数疲劳方程比单对数方程的预测效果更好。