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Sensor-based time-dependent formation factor in prediction of chloride ingress in mortar

机译:基于传感器的时间依赖性形成系数,预测砂浆氯化物进入

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摘要

Characterisation of chloride ingress rate is crucial for service life predictions in reinforced concrete. In this study, the time-dependent chloride diffusion coefficient (D-Cl(t)) was determined using real-time non-destructive embedded sensors. First, the time-dependent formation factor was established based on continuous electrical conductivity data from the sensors, which provided D-Cl(t) by the Nernst-Einstein equation. Twelve mortar mixtures were included that varied in water/cementitious materials ratio (w/c) and supplementary cementitious material (SCM) content. A numerical model of chloride diffusion using the established D-Cl(t) was developed by solving Fick's second law of diffusion using the finite-difference method. The model's predictions agreed well with experimental chloride profiles available in the literature. The results of chloride ingress simulation for all tested mixtures clearly showed the effect of reducing the w/c and using more SCM on slowing the rate of chloride ingress. Furthermore, the developed D-Cl(t) relations were used to establish a diffusion decay coefficient (m(diff)) for all tested mixtures, leading to the development of empirical formulations for D-Cl(t) and m(diff) as a function of w/c and SCM content. The results of this study demonstrate the potential of the implemented non-destructive technique in efficient assessment of transport properties of mortar related to chloride ingress.
机译:氯化物入口率的表征对于钢筋混凝土中的使用寿命预测至关重要。在该研究中,使用实时无损嵌入式传感器测定时间依赖性氯化物扩散系数(D-CL(T))。首先,基于来自传感器的连续电导率数据建立时间依赖性形成系数,该数据由NERNST-EINSTEIN方程提供D-CL(T)。包含12个砂浆混合物,其在水/水泥材料比(W / C)和补充水泥材料(SCM)含量中变化。通过使用有限差分法解决Fick的第二次扩散定律,开发了使用已建立的D-CL(T)的氯化物扩散的数值模型。该模型的预测与文献中可用的实验氯化物型材很好地商定。所有测试混合物的氯化物入口模拟结果清楚地表明了减少W / C的效果,并使用更多SCM放缓氯化物进入速度。此外,开发的D-CL(T)关系用于建立所有测试混合物的扩散衰减系数(M(差异)),从而导致D-C1(T)和M(Diff)的经验制剂的发展W / C和SCM内容的函数。该研究的结果证明了实施的非破坏性技术的潜力,以有效评估迫击砂浆与氯化物进入相关的运输特性。

著录项

  • 来源
    《Magazine of Concrete Research》 |2019年第22期|1180-1192|共13页
  • 作者单位

    Washington State Univ Pullman WA 99164 USA;

    Washington State Univ Pullman WA 99164 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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