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Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images./
作者:	Sharma, Shivam.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	201 p.
附註:	Source: Masters Abstracts International, Volume: 83-02.
Contained By:	Masters Abstracts International83-02.
標題:	Civil engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28490989
ISBN:	9798534691276

Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images.
Sharma, Shivam.

Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 201 p.

Source: Masters Abstracts International, Volume: 83-02.

Thesis (M.S.)--University of Maryland, College Park, 2021.

This item must not be sold to any third party vendors.

The objective of this research was to determine which image processing algorithms were most effective in quantifying the microcrack distribution in concrete in laser shearography images.The motivation is the need for a nondestructive method to measure the development of damage in concrete due to expansive stresses generated by delayed ettringite formation (D.E.F.). This produces networks of fine microcracks. These may not be visible to the human eye or detectable by conventional imaging techniques. However, laser shearography provides a means to visualize them at very early stages of growth. This nondestructive method generates a first derivative image of the surface topography. This can make cracks less than 1 µm visible. These can in turn be quantified by automated image processing algorithms. These crack pattern images can then be analyzed to obtain sets of statistics that can be tracked over time for investigating the D.E.F. process which can provide insights into the crack propagation mechanisms. This research thus concerned the application of automated image processing to a set of laser shearography images of concrete prisms where D.E.F. damage had been induced by an accelerated test method. Four prisms were involved. Two were treated to accelerate the D.E.F. rate of development. The other two were controls. They were imaged periodically at roughly month intervals by laser shearography for up to 200 days. A commercial automated image processing software, ImagePro was used. Two approaches were tried to identify the cracks in each image: manually or by an automated macro. Once a crack was identified, its track was traced by an auto tracing algorithm. It was found that the macro generated too many artifacts, so the manual method was used. The results showed significant differences between the control prisms and the treated ones in terms of crack numbers and their length. Over time the cracks in the treated specimens tended to grow longer but fewer in number as the individual cracks joined up. In the controls, the cracks tended to disappear with time. This may be because they were only superficial in the first place and then were covered by a thin surface layer of calcium hydroxide that precipitated from the lime water bath. The conclusion is that it is feasible to apply automated imaging techniques to quantify damage due to D.E.F. However, a disadvantage of using the existing commercial software was that it produced crack tracks that were only one pixel wide. Thus, it was not possible to measure actual crack width and their changes with expansion. Another issue is that it is designed for images of surfaces in real space whereas the laser shearography image is the first derivative of the surface topography. This contains information that could be used to estimate crack widths. It could also be used to automate the detection of cracks, possibly by the application of artificial intelligence techniques.

ISBN: 9798534691276Subjects--Topical Terms:

860360
Civil engineering.
Subjects--Index Terms:

Microcrack

Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images.
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500 $a Source: Masters Abstracts International, Volume: 83-02.
500 $a Includes supplementary digital materials.
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502 $a Thesis (M.S.)--University of Maryland, College Park, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a The objective of this research was to determine which image processing algorithms were most effective in quantifying the microcrack distribution in concrete in laser shearography images.The motivation is the need for a nondestructive method to measure the development of damage in concrete due to expansive stresses generated by delayed ettringite formation (D.E.F.). This produces networks of fine microcracks. These may not be visible to the human eye or detectable by conventional imaging techniques. However, laser shearography provides a means to visualize them at very early stages of growth. This nondestructive method generates a first derivative image of the surface topography. This can make cracks less than 1 µm visible. These can in turn be quantified by automated image processing algorithms. These crack pattern images can then be analyzed to obtain sets of statistics that can be tracked over time for investigating the D.E.F. process which can provide insights into the crack propagation mechanisms. This research thus concerned the application of automated image processing to a set of laser shearography images of concrete prisms where D.E.F. damage had been induced by an accelerated test method. Four prisms were involved. Two were treated to accelerate the D.E.F. rate of development. The other two were controls. They were imaged periodically at roughly month intervals by laser shearography for up to 200 days. A commercial automated image processing software, ImagePro was used. Two approaches were tried to identify the cracks in each image: manually or by an automated macro. Once a crack was identified, its track was traced by an auto tracing algorithm. It was found that the macro generated too many artifacts, so the manual method was used. The results showed significant differences between the control prisms and the treated ones in terms of crack numbers and their length. Over time the cracks in the treated specimens tended to grow longer but fewer in number as the individual cracks joined up. In the controls, the cracks tended to disappear with time. This may be because they were only superficial in the first place and then were covered by a thin surface layer of calcium hydroxide that precipitated from the lime water bath. The conclusion is that it is feasible to apply automated imaging techniques to quantify damage due to D.E.F. However, a disadvantage of using the existing commercial software was that it produced crack tracks that were only one pixel wide. Thus, it was not possible to measure actual crack width and their changes with expansion. Another issue is that it is designed for images of surfaces in real space whereas the laser shearography image is the first derivative of the surface topography. This contains information that could be used to estimate crack widths. It could also be used to automate the detection of cracks, possibly by the application of artificial intelligence techniques.
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