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弥散超声在评价裂缝混凝土水渗透性和氯离子渗透性中的适用性。

Applicability of Diffuse Ultrasound to Evaluation of the Water Permeability and Chloride Ion Penetrability of Cracked Concrete.

机构信息

School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea.

出版信息

Sensors (Basel). 2018 Nov 27;18(12):4156. doi: 10.3390/s18124156.

DOI:10.3390/s18124156
PMID:30486390
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6308831/
Abstract

This study aims to explore the applicability of diffuse ultrasound to the evaluation of water permeability and chloride ion penetrability of cracked concrete. Lab-scale experiments were conducted on disk-shaped concrete specimens, each having a different width of a penetrating crack that was generated by splitting tension along the centerline. The average crack width of each specimen was determined using an image binarization technique. The diffuse ultrasound test employed signals in the frequency range of 200 to 440 kHz. The water flow rate was measured using a constant water-head permeability method, and the chloride diffusion coefficient was determined using a modified steady-state migration method. Then, the effects of crack width on the diffusion characteristics of ultrasound (i.e., diffusivity, dissipation), water flow rate, and chloride diffusion coefficient are investigated. The correlations between the water flow rate and diffuse ultrasound parameters, and between the chloride diffusion coefficient and diffuse ultrasound parameters, are examined. The results suggest that diffuse ultrasound is a promising method for assessing the water permeability and chloride ion penetrability of cracked concrete.

摘要

本研究旨在探讨漫射超声在评估开裂混凝土的水渗透性和氯离子渗透性中的适用性。通过对具有不同贯穿裂缝宽度的圆盘状混凝土试件进行实验室规模的试验，这些裂缝是通过沿中心线的劈裂拉伸产生的。采用图像二值化技术确定每个试件的平均裂缝宽度。漫射超声测试采用 200 至 440 kHz 频率范围内的信号。采用恒水头渗透法测量水流速率，采用改进的稳态迁移法确定氯离子扩散系数。然后，研究了裂缝宽度对超声（即扩散率、耗散率）、水流速率和氯离子扩散系数扩散特性的影响。检验了水流速率与漫射超声参数之间以及氯离子扩散系数与漫射超声参数之间的相关性。结果表明，漫射超声是评估开裂混凝土水渗透性和氯离子渗透性的一种很有前途的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/43e5d992b134/sensors-18-04156-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/6ec179b50366/sensors-18-04156-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/9d7a7fe870e6/sensors-18-04156-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/0b0e08442c98/sensors-18-04156-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/216cb2a93d84/sensors-18-04156-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/3f47b91bad22/sensors-18-04156-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/e0b973df363f/sensors-18-04156-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/5ca606ad675a/sensors-18-04156-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/43e5d992b134/sensors-18-04156-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/857a8d98d209/sensors-18-04156-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/b8002a3875e7/sensors-18-04156-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/87e1e47b7684/sensors-18-04156-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/b2de501ff68b/sensors-18-04156-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/6ec179b50366/sensors-18-04156-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/9d7a7fe870e6/sensors-18-04156-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/0b0e08442c98/sensors-18-04156-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/216cb2a93d84/sensors-18-04156-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/3f47b91bad22/sensors-18-04156-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/e0b973df363f/sensors-18-04156-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/5ca606ad675a/sensors-18-04156-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b7b/6308831/43e5d992b134/sensors-18-04156-g012.jpg

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本文引用的文献

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Surface-Wave Based Model for Estimation of Discontinuity Depth in Concrete.基于表面波的混凝土不连续性深度估计模型。
Sensors (Basel). 2018 Aug 24;18(9):2793. doi: 10.3390/s18092793.
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Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.使用结合混合图像处理的无人机进行混凝土裂缝识别
Sensors (Basel). 2017 Sep 7;17(9):2052. doi: 10.3390/s17092052.
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Principles and Applications of Ultrasonic-Based Nondestructive Methods for Self-Healing in Cementitious Materials.基于超声波的水泥基材料自修复无损检测方法的原理与应用
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