國立虎尾科技大學 |

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

紀錄類型:	書目-語言資料,印刷品 : 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:

561339
Civil engineering.
Subjects--Index Terms:

Microcrack

Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images.
LDR:04279nam a2200409 4500 001 1067180
005 20220823142309.5
008 221020s2021 ||||||||||||||||| ||eng d
020 $a 9798534691276
035 $a (MiAaPQ)AAI28490989
035 $a AAI28490989
040 $a MiAaPQ $c MiAaPQ
100 1 $a Sharma, Shivam. $0 (orcid)0000-0002-8558-4791 $3 1372557
245 1 0 $a Quantitative Analysis of Microcracks in Concrete from Delayed Ettringite Formation by Image Processing of Laser Shearography Images.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 201 p.
500 $a Source: Masters Abstracts International, Volume: 83-02.
500 $a Includes supplementary digital materials.
500 $a Advisor: Amde, Amde M.;Livingston, Richard.
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.
590 $a School code: 0117.
650 4 $a Civil engineering. $3 561339
650 4 $a Materials science. $3 557839
650 4 $a Geographic information science. $3 1372545
650 4 $a Mechanical engineering. $3 557493
650 4 $a Software. $2 gtt $3 574116
650 4 $a Values. $3 554790
650 4 $a Concrete. $3 867676
650 4 $a Calibration. $3 1027585
650 4 $a Heat. $3 1276837
650 4 $a Noise. $3 671314
650 4 $a Potassium. $3 1372559
650 4 $a Cracks. $3 1372560
650 4 $a Aerospace engineering. $3 686400
650 4 $a Hydration. $3 778453
650 4 $a Interferometry. $3 643415
650 4 $a Fourier transforms. $3 1372561
650 4 $a Lasers. $3 557748
650 4 $a Data collection. $3 1372505
650 4 $a Cement. $3 785099
650 4 $a Potash. $3 1372562
650 4 $a Curing. $3 1372563
650 4 $a Bridges. $3 1028796
653 $a Microcrack
653 $a Concrete
653 $a Ettringite formation
653 $a Image processing
653 $a Laser shearography images
690 $a 0543
690 $a 0794
690 $a 0548
690 $a 0370
690 $a 0538
710 2 $a University of Maryland, College Park. $b Civil Engineering. $3 1372558
773 0 $t Masters Abstracts International $g 83-02.
790 $a 0117
791 $a M.S.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28490989