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再生骨料初始强度对再生混凝土力学性能的影响 被引量:3

Effect of Recycled Aggregate Initial Strength on Mechanical Properties of Recycled Concrete
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摘要 为了研究再生骨料初始强度和替代率对再生混凝土性能的影响,采用3种初始强度等级的再生骨料(C20、C30、C50),考虑3种再生骨料替代率,设计了7种配合比的混凝土,对再生混凝土的和易性、吸水率、超声脉冲速度(UPV)、力学性能(抗压强度、劈裂抗拉强度)进行了评估。试验结果表明:再生骨料的掺入对混凝土产生了负面影响,随着再生骨料替代率的增加,再生混凝土的和易性和质量逐渐变差,抗压强度和劈裂抗拉强度逐渐降低,但提高再生混凝土的初始强度在一定程度上可以改善再生混凝土的和易性、质量和力学性能。通过对试验数据的拟合,得到不同再生骨料初始强度与替代率的再生混凝土抗压强度与劈裂抗拉强度预测模型。 In order to study the influence of the initial strength and substitution rate of recycled aggregate on the performance of recycled concrete,three kinds of recycled aggregate with different initial strength grades(C20,C30,C50)are used,and considering the replacement rate of three kinds of recycled aggregate,seven kinds of mixing ratio concrete are designed to evaluate the workability,water absorption,ultrasonic pulse velocity(UPV),mechanical properties(compressive strength,splitting tensile strength)of recycled concrete.The experimental results show that the addition of recycled aggregate has a negative impact on concrete.With the increase of recycled aggregate replacement rate,the workability and quality of recycled concrete gradually deteriorate,and the compressive strength and splitting tensile strength gradually decrease.However,increasing the initial strength of recycled concrete can improve the workability,quality and mechanical properties of recycled concrete to some extent.By fitting the experimental data,the prediction models of compressive strength and splitting tensile strength of recycled concrete with different initial strength and replacement rate of recycled aggregate are obtained.
作者 魏晋珍 靳高明 刘生纬 WEI Jin-zhen;JIN Gao-ming;LIU Sheng-wei(Gansu Jiantou Construction Co.Ltd.,Lanzhou 730070,China;Research Institute of Lanzhou Jiaotong University,Lanzhou 730070,China)
出处 《公路》 北大核心 2023年第6期378-384,共7页 Highway
基金 甘肃省科技计划资助,项目编号20YF8GA009 住房和城乡建设部2021年科学技术计划,项目编号2021-K-011。
关键词 再生混凝土 初始强度 再生骨料替代率 力学性能 强度预测模型 recycled aggregate concrete initial strength replacement rate of recycled aggregate mechanical properties strength prediction model
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