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A probabilistic analysis of acoustic emission events and associated energy release during formation of shear and tensile cracks in cementitious materials under uniaxial compression
- Source :
- Journal of Building Engineering. 20:647-662
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- The study of classification of cracks in concrete structures is considered to be important to predict the type of failure that could occur under the various loading conditions. It is useful in the damage assessment studies related to concrete structures and in the implementation of appropriate rehabilitation methods for the service life extension. In this study, several specimen of cement concrete , mortar were tested under uniaxial compression and simultaneously the released acoustic emissions (AE) were recorded. To study crack classification in cementitious materials under uniaxial compression, Gaussian Mixture Modeling (GMM) algorithm was used to separate the released AE during formation of tensile type and shear type microcracks . The influence of coarse aggregate size, curing period and rate of loading on AE characteristics has been studied. The separated AE energy released during tensile type cracking and shear type cracking was used to study the failure of the cementitious materials. The crack classification study related to concrete structures is useful to get an early warning prior to final failure.
- Subjects :
- Cement
Materials science
0211 other engineering and technologies
020101 civil engineering
02 engineering and technology
Building and Construction
0201 civil engineering
Cracking
Shear (geology)
Acoustic emission
Mechanics of Materials
021105 building & construction
Architecture
Ultimate tensile strength
Service life
Cementitious
Composite material
Mortar
Safety, Risk, Reliability and Quality
Civil and Structural Engineering
Subjects
Details
- ISSN :
- 23527102
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- Journal of Building Engineering
- Accession number :
- edsair.doi...........308907cbffdf1a23ece44dc615787928