Characterization of crack networks in desiccating soils using image analysis techniques

被引:0
|
作者
Lakshmikantha, M. R. [1 ]
Prat, P. C. [1 ]
Ledesma, A. [1 ]
机构
[1] Tech Univ Catalonia, Barcelona, Spain
关键词
D O I
暂无
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Image analysis techniques can be applied to study the crack patterns that appear in cohesive soils under drying conditions due to changes in the environmental conditions. Qualitative and quantitative characterization of these crack networks is needed to study the mechanical behavior of a cracking soil, how cracks generate and propagate. The paper describes a simple technique to process sequences of images obtained during laboratory tests, and how information can be gathered by means of image analysis, including average crack width, total crack length, total area of cracks, number, area and aspect ratio of un-cracked cells, surface shrinkage, etc. Crack initiation and time evolution of the crack pattern can also be determined. An example of application that shows size-effect in the drying of soils is presented.
引用
收藏
页码:167 / 173
页数:7
相关论文
共 50 条
  • [21] Morphological characterization of flowing particles by image analysis techniques
    Bonifazi, G
    Francini, F
    Guarnieri, V
    Longobardi, G
    Massacci, P
    Recinella, M
    PARTICLE & PARTICLE SYSTEMS CHARACTERIZATION, 1995, 12 (06) : 318 - 323
  • [22] Microstructural characterization of cemented carbides by image analysis techniques
    Ghosh, D.
    Metal Powder Report, 2001, 56 (03)
  • [23] STRUCTURAL CHARACTERIZATION OF ELECTROSPUN SCAFFOLDS BY IMAGE ANALYSIS TECHNIQUES
    Vatankhah, Elham
    Semnani, Dariush
    Tadayon, Mahdi
    2012 9TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 2012, : 1381 - 1384
  • [24] Crack Length Measurement Using Convolutional Neural Networks and Image Processing
    Yuan, Yingtao
    Ge, Zhendong
    Su, Xin
    Guo, Xiang
    Suo, Tao
    Liu, Yan
    Yu, Qifeng
    SENSORS, 2021, 21 (17)
  • [25] Crack Width Measurement Using Unified Image Processing Techniques for Aging Structures
    Argosino, Jeremy A.
    Capistrano, Marie Aila B.
    Salido, Lisette S.
    Villaverde, Jocelyn Flores
    Paglinawan, Arnold C.
    PROCEEDINGS OF 2020 12TH INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2020), 2020, : 90 - 93
  • [26] Application of New Feature Techniques for Multimedia Analysis in Artificial Neural Networks by Using Image Processing
    Liu, Lianqiu
    Yang, Yongping
    Chen, Hong Shun
    Informatica (Slovenia), 2024, 48 (11): : 113 - 124
  • [27] Analysis of Crack Coalescence in Concrete Using Neural Networks
    H. Haeri
    V. Sarfarazi
    Z. Zhu
    Strength of Materials, 2016, 48 : 850 - 861
  • [28] Analysis of Crack Coalescence in Concrete Using Neural Networks
    Haeri, H.
    Sarfarazi, V.
    Zhu, Z.
    STRENGTH OF MATERIALS, 2016, 48 (06) : 850 - 861
  • [29] Finding the temperature using image analysis techniques
    Oprisan, Ana
    Oprisan, Sorinel A.
    Hegseth, John
    Garrabos, Yves
    Beysens, Daniel
    MATHEMATICS OF DATA/IMAGE PATTERN RECOGNITION, COMPRESSION, AND ENCRYPTION WITH APPLICATIONS XI, 2008, 7075
  • [30] POTENTIAL DROP TECHNIQUES FOR CRACK CHARACTERIZATION
    WOJCIK, AG
    MATERIALS WORLD, 1995, 3 (08) : 379 - 381