不同温度下低热混凝土强度及孔结构分形特征研究
Study on strength and pore structure fractal characteristics of low-heat concrete with different temperature
关彬 1陈博夫 2刘硕3
作者信息
- 1. 河海大学水利水电学院,江苏南京 210098
- 2. 三峡大学水利与环境学院,湖北宜昌 443002
- 3. 湖北能源集团南漳张家坪抽水蓄能公司,湖北襄阳 441500
- 折叠
摘要
[目的]为探究真实温度环境下低热混凝土微观演化规律与宏观力学性能之间的关系,[方法]设计并开展了不同温度(20℃、30 ℃、40℃)作用下低热混凝土抗压强度和孔结构试验,基于扫描电镜(SEM)图像,结合盒维数法,计算得到了低热混凝土的分形维数,最后建立了考虑分形维数的抗压强度预测模型.[结果]结果显示:高温养护下,低热混凝土的临界孔径、最可几孔径和孔隙率降低,分形维数从1.796 8增加到1.886 8,28 d抗压强度增长了 27％.[结论]结果表明,36％～42％的孔隙率和10～20 nm的孔径对应的微观空间状态最为复杂,高温养护增强低热混凝土 10～20 nm的孔径含量,有效提高了抗压强度;提出的预测模型可以定量描述低热混凝土力学性能与孔结构分形维数的耦联关系,为不同温度作用下大坝混凝土的耐久性和安全性设计提供了理论支撑.
Abstract
[Objective]In order to explore the relationship between microscopic structure evolution law and macroscopic mechani-cal properties of low-heat concrete under real temperature environment,[Methods]the compressive strength and pore structure tests of low-heat concrete under different temperatures(20 ℃,30 ℃,40 ℃)were designed and carried out.Based on the scanning electron microscope(SEM)images,the fractal dimension of low-heat concrete was calculated by the box dimension method.Finally,a compressive strength prediction model considering fractal dimension was established.[Results]The results show that under high temperature curing,the most probable pore diameter and porosity decrease,the fractal dimension increases from 1.796 8 to 1.886 8,and the compressive strength increases significantly.[Conclusion]The microscopic space state corre-sponding to 36％～42％porosity and 10～20 nm pore diameter is most complex,high temperature curing increases the pore size content of 10～20 nm and effectively improves the compressive strength.The prediction model can quantitatively describe the cou-pling relationship between mechanical properties of low-heat concrete and fractal dimension of pore structure,which provide theo-retical support for the durability and safety design of dam concrete under different temperatures.
关键词
低热混凝土/温度/孔结构/分形维数/预测模型/力学性能Key words
low-heat concrete/temperature/pore structure/fractal dimension/prediction model/mechanical properties引用本文复制引用
基金项目
国家自然科学基金青年项目(52109158)
出版年
2024
国家科技期刊平台
NSTL
万方数据