The use of computerized tomography (CT) and image processing for evaluation of the properties of foam concrete produced with different content of foaming agent and aggregate

被引:15
作者
Gencel, Osman [1 ]
Nodehi, Mehrab [2 ]
Bozkurt, Ahmet [3 ]
Sari, Ahmet [4 ,5 ]
Ozbakkaloglu, Togay [6 ]
机构
[1] Bartin Univ, Fac Engn Architecture & Design, Civil Engn Dept, TR-74100 Bartin, Turkiye
[2] Univ Calif Davis, Dept Civil & Environm Engn, Davis, CA 95616 USA
[3] Istanbul Tech Univ, Informat Inst, Div Computat Sci & Engn, TR-34467 Istanbul, Turkiye
[4] Karadeniz Tech Univ, Dept Met & Mat Engn, TR-61080 Trabzon, Turkiye
[5] King Fahd Univ Petr & Minerals, Interdisciplinary Res Ctr Renewable Energy & Power, Dhahran, Saudi Arabia
[6] Texas State Univ, Ingram Sch Engn, San Marcos, TX 78666 USA
关键词
Image processing; Computerized tomography (CT) scan; Foam concrete; Porosity;
D O I
10.1016/j.conbuildmat.2023.132433
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study measures the impact of foaming agent and aggregate content in foam concrete mixes by conducting a series of tests on material properties as well as pore formation by using micro-Computerized Tomography (CT) scanning and image processing technique. This technique allows measuring the porosity fraction of porous materials and foam concretes to comparatively evaluate the experimental versus the image processed porosity of the samples. Based on the results, it is found that the increase in aggregate content can exponentially reduce the pore connectivity of foams and enhance their physical and mechanical properties. Additionally, the proposed CT scanning and image processing approach is a proof-of-concept over the use of 3D modeling. This is done with a specific tool-kit and the results prove suitability of image processing techniques in accurately measuring pore content in foam concrete samples. Suggestions for future studies are also provided and discussed at the end of the manuscript.
引用
收藏
页数:18
相关论文
共 30 条
[21]   Concrete Crack Detection Algorithm Based on Deep Residual Neural Networks [J].
Meng, Xiuying .
SCIENTIFIC PROGRAMMING, 2021, 2021
[22]   A systematic review of bacteria-based self-healing concrete: Biomineralization, mechanical, and durability properties [J].
Nodehi, Mehrab ;
Ozbakkaloglu, Togay ;
Gholampour, Aliakbar .
JOURNAL OF BUILDING ENGINEERING, 2022, 49
[23]   A comparative review on foam-based versus lightweight aggregate-based alkali-activated materials and geopolymer [J].
Nodehi, Mehrab .
INNOVATIVE INFRASTRUCTURE SOLUTIONS, 2021, 6 (04)
[24]   Cellular concrete properties and the effect of synthetic and protein foaming agents [J].
Panesar, D. K. .
CONSTRUCTION AND BUILDING MATERIALS, 2013, 44 :575-584
[25]   Finite Element Modeling of Chloride Diffusion in Concrete Using Image Processing for Characterizing Real Shape and Distribution of Different Phases [J].
Razmjoo, A. ;
Poursaee, A. .
ADVANCES IN CIVIL ENGINEERING MATERIALS, 2016, 5 (01) :167-178
[26]   Nondestructive test methods for concrete bridges: A review [J].
Rehman, Sardar Kashif Ur ;
Ibrahim, Zainah ;
Memon, Shazim Ali ;
Jameel, Mohammed .
CONSTRUCTION AND BUILDING MATERIALS, 2016, 107 :58-86
[27]  
Stovall T, 2012, CLOSED CELL FOAM INS, DOI [10.2172/1093061, DOI 10.2172/1093061]
[28]   Automated bughole detection and quality performance assessment of concrete using image processing and deep convolutional neural networks [J].
Wei, Wei ;
Ding, Lieyun ;
Luo, Hanbin ;
Li, Chen ;
Li, Guowei .
CONSTRUCTION AND BUILDING MATERIALS, 2021, 281
[29]   Finite element model of concrete material based on CT image processing technology [J].
Yang, Wenwei .
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2019, 64
[30]   Fluidity and strength behaviors of cemented foam backfill: effect of particle size distribution and foaming agent dosage [J].
Zhang, Shiyu ;
Yang, Lei ;
Qiu, Jingping ;
Hou, Chen ;
Guo, Zhenbang .
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2021, 80 (04) :3177-3191