Skip to Main content Skip to Navigation
Theses

Identification and tracking of grains undergoing progressive breakage under mechanical loading with image analysis of 3D+t tomographic images

Abstract : Grain breakage in granular materials has been relatively, difficult to compute and characterise in tomography images. This is based on the perceived complexity of an algorithmic formulation for the characterisation of grains that move and break.In this thesis, we highlight computational approaches that augment the understanding of breakage and crushing phenomena in granular materials. Due to the inter-connectedness of segmentation accuracy and ability to compute for breakage, we start by examining noise removal techniques in granular materials. Noise removal techniques are analysed based on a set of materials to which they applied. Secondly, we deviate from a morphological watershed approach to segmentation of geomaterials, to a hierarchical approach that better captures apriori information from data sources. The ways by which context or image specific segmentation can be achieved is iterated. Thirdly, we present a model for capturing breakage in static images; without the consideration of motion. Finally, we present spatiotemporal models that track the evolution of breakage in images of granular materials.
Document type :
Theses
Complete list of metadatas

Cited literature [143 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-02438210
Contributor : Abes Star :  Contact
Submitted on : Tuesday, January 14, 2020 - 10:26:10 AM
Last modification on : Wednesday, October 14, 2020 - 4:19:54 AM
Long-term archiving on: : Wednesday, April 15, 2020 - 2:32:37 PM

File

OKUBADEJO__2019_archivage.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-02438210, version 1

Collections

STAR | UGA | 3S-R | CNRS

Citation

Olumide Okubadejo. Identification and tracking of grains undergoing progressive breakage under mechanical loading with image analysis of 3D+t tomographic images. Material chemistry. Université Grenoble Alpes, 2019. English. ⟨NNT : 2019GREAI053⟩. ⟨tel-02438210⟩

Share

Metrics

Record views

107

Files downloads

59