WEBJul 1, 1980 · Estimates of these parameters can be made from imagebased threedimensional (3D) characterization of coal cleats using Xray microcomputed tomography (μCT). One key step in this process, after cleat extraction, is the separation of individual cleats, without which the cleats are a connected network and statistics for different .
WEBApr 21, 2022 · A forwardperceptive neural network model based on a convolutional neural network and attentionbased layer structure that enhances the noise reduction capability of classical neural networks by forward perceptive design and uses pixellevel perceptual neurons to ensure that the distribution of effective pixel points is not affected during the .
WEBOct 1, 2015 · A workflow for extracting coal cleats, including sample preparation, image acquisition, and image processing has been established (Ramandi et al., 2015;Mostaghimi et al., 2017). ...
WEBImage processing based characterization of coal cleat networks. International Journal of Coal Geology (2017). link. 2016. H M D Harshani, S A GalindoTorres, A Scheuermann and H B Muhlhaus. Experimental study of porous media flow using hydrogel beads and LED based PIV. Measurement Science and Technology (2016), Volume 28, Number 1.
WEBDec 1, 2019 · Coal permeability is known to be affected by the sorptioninduced strain. Indeed, coal swells with gas sorption and shrinks with desorption, which is likely to modify the cleat aperture and thus the permeability. Coal permeability evolution is crucially important for either Coalbed Methane production (CBM) or Carbon dioxide Capture and .
WEBDOI: / Corpus ID: ; Quantitative characterization of fracture structure in coal based on image processing and multifractal theory article{Guoxi2020QuantitativeCO, title={Quantitative characterization of fracture structure in coal based on image processing and multifractal theory}, author={Chen .
WEBselect article Image processing based characterisation of coal cleat networks. ... Research article Full text access Image processing based characterisation of coal cleat networks. J. Busse, de Dreuzy, S. Galindo Torres, D. Bringemeier, A. Scheuermann. Pages 121 View PDF.
WEBDOI: / Corpus ID: ; Coal cleat reconstruction using microcomputed tomography imaging article{Jing2016CoalCR, title={Coal cleat reconstruction using microcomputed tomography imaging}, author={Yu Jing and Ryan T. Armstrong and Hamed Lamei Ramandi and Peyman Mostaghimi}, journal={Fuel}, .
WEBImage processing based characterisation of coal cleat networks ... seam properties which in turn are fundamental for flow and geomechanical modelling in the context of underground coal mining ...
WEBThe marked area in b is shown in Figure 8. "Image processing based characterisation of coal cleat networks" Figure 7 a. Dilated and b. eroded binary image of sample E2. ... {Image processing based characterisation of coal cleat networks}, author={Julia Busse and JeanRaynald de Dreuzy and Sergio A. G. Torres and Detlef Bringemeier and ...
WEBGalindo Sergio., Bringemeier D. and Scheuermann A., Image processing based characterisation of coal cleat networks, ... An approach on determination on coal quality using digital image processing, Int. Journal of Engineering Research and Appliions 5 (12) (2015), 38 ...
WEBOct 18, 2019 · Characterization of coal microstructure and the associated rock mechanical properties are of key importance for coal seam exploration, coal bed methane development, enhanced coal bed methane production and CO2 storage in deep coal seams. Considerable knowledge exists about coal chemical properties, but less is .
WEBMay 1, 2023 · Characterisation of the cleat network serves as the basis for estimating the hydraulic and mechanical seam properties which in turn are fundamental for flow and geomechanical modelling in the ...
WEBDOI: / Corpus ID: ; Image processing based characterisation of coal cleat networks article{Busse2017ImagePB, title={Image processing based characterisation of coal cleat networks}, author={Julia Busse and JeanRaynald de Dreuzy and Sergio A. G. Torres and Detlef Bringemeier and Alexander .
WEBAug 2, 2019 · In this study, the postprocessing methods (image processing, 3D reconstruction, numerical simulation, etc.) of CT scan images are introduced in detail, and the appliion of CT in the coal ...
WEBJan 1, 2004 · Coal characteristics analysed in this paper include cleat geometry, topology of cleat network, degree of mineralisation, and roughness of cleat surfaces. MicroCT scanning procedures to obtain ...
WEBAug 1, 2020 · An image processing technique was used to obtain highresolution fracture images (with an actual resolution of approximately 2 μm), followed by the statistics of the porosity parameters such as microfracture density, intersection point density, and plane areal porosity. ... Image processing based characterisation of coal cleat networks. .
WEBMar 1, 2017 · Its production is mainly controlled by the underlying fracture network of coal, called "cleats". The discrete fracture network (DFN) model is widely applied for characterising fracture networks due to its ability of accounting for physical geological parameters of cleats. ... The microCT image acquisition and processing are described .
WEBOct 3, 2019 · The formation of cleats in coal has started to occur by many mechanisms in various periods of coal, but the presence of one mayor fault and three minor faults trending NESW in the mine pit are ...
WEBJan 1, 2022 · Coal Cleat/Fracture Segmentation Using Convolutional Neural Networks. This study uses CNNbased methods to segment cleats/fractures of two types of coal samples: homogenous (with typical cleat system) and heterogeneous (with complex background and irregular fracture system). Expand.
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