Coke optical texture as the fractal object

Piechaczek, M.; Mianowski, A.

doi:10.1016/j.fuel.2017.01.081

Cited by 14 publications

(10 citation statements)

References 17 publications

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“…In nonmicrowave studies, similar values of reflectance have been observed for laboratory-scale experiments in a Jenkner retort oven . Piechaczek et al used petrographic analysis to assess anisotropy, which showed similar textures to those observed in this study, and showed that the multifractal dimension of texture correlates strongly with reflectance and CRI/CSR …”

Section: Resultssupporting

confidence: 81%

“…53 Piechaczek et al 9 used petrographic analysis to assess anisotropy, which showed similar textures to those observed in this study, and showed that the multifractal dimension of texture correlates strongly with reflectance and CRI/CSR. 54 Table 5 summarizes the proximate analysis and intrinsic reactivity of the coals before treatment as well as the impact of the various treatments on their properties compared to the commercial coke. No moisture remained in the samples after the treatment, and all the samples showed lower volatile contents than the conventional UK Coke for all treatment conditions.…”

Section: Energy and Fuelsmentioning

confidence: 99%

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Formation of Metallurgical Coke within Minutes through Coal Densification and Microwave Energy

Williams

Ure²,

Stevens

et al. 2019

Energy Fuels

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This paper shows how feedstock densification gives rise to a step change in the time required to create a metallurgical grade coke using microwave energy. Five densified coking and noncoking coals were heated in a multi-mode microwave 2450 MHz cavity for varying treatment times (2-20 minutes) with a fixed power input (6 kW). Proximate analysis, intrinsic reactivity, coke reactivity, dielectric properties, and petrographic analysis of the coals and microwave produced lump cokes were compared to a commercial lump coke. Densifying the sample prior to microwave treatment enabled a dramatic acceleration of the coking process when combined with targeted high microwave energy densities. It was possible to form fused coke lump structures with only 2 minutes of microwave heating compared to 16-24 hours via conventional coking. Anisotropic coke morphologies (lenticular and circular) were formed from non-coking coal that are not possible with conventional coking and increasing treatment time improved overall coke reflectance. Three of the coals produced coke with equivalent coke reactivity index values of 20-30, which are in the acceptable range for blast furnaces. The study demonstrated that via this process, non-coking coals could potentially be used to produce high quality cokes, potentially expanding the raw material options for metallurgical coke production.

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Section: Resultssupporting

confidence: 81%

Section: Energy and Fuelsmentioning

confidence: 99%

Formation of Metallurgical Coke within Minutes through Coal Densification and Microwave Energy

Williams

Ure²,

Stevens

et al. 2019

Energy Fuels

View full text Add to dashboard Cite

show abstract

“…26 Clearly, reflectance increases during combustion, and higher maximum reflectance values indicate a more ordered carbon molecular structure. 27 Reflectance is also commonly used to establish coke quality 28 because there is a direct link between the reflectance of the coke and the furnace conditions used, as well as coal maturity. 29 Charcoal reflectance was shown to be a way to determine the regional intensity of wildfires 30 where reflectance levels were found to be the greatest in areas that had experienced the most severe fires.…”

Section: Introductionmentioning

confidence: 99%

Novel Thermal and Microscopic Techniques To Determine the Causes of Suboptimal Combustion Performance at Colombian Stoker Furnaces

et al. 2022

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This study presents the application of a novel approach, using thermal and optical techniques, to identify the causes of poor burnout performance of Colombian stoker furnaces in the Cauca Valley State. The four coals used in these furnaces were characterized to obtain particle size distribution, particle and tapped density, elemental and proximate composition, mineral composition, and maceral content. Up to 80% incomplete combustion was noted in macro-TGA tests compared to complete combustion in a micro-TGA. Reflectance and intrinsic reactivity measurements were for chars prepared in three different particle sizes (<6, 6–19, and 19 mm), three temperatures (700, 900, and 1050 °C), and three residence times (10, 30, and 120 min). Two of the coals produced char samples with reflectance values above 6%, which matched those seen in the stoker, indicating that the furnace temperature was not the cause of poor combustion and that only two of the four coals were likely to be present in the furnace bottom ash. These tests were also able to prove that oxygen diffusion limitation was the root cause of the poor burnout where the carbon inside the furnace bottom ash was shielded from oxygen ingress through the formation of a nonpermeable slag layer. Thus, this study demonstrates the potential of both thermal profiling and optical reflectance as a tool for forensically evaluating the thermal history and operational performance of furnaces.

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“…Two calculation procedures are most frequently applied: box counting and gliding box. The application of multifractal analysis to color images is predominantly reduced to the conversion into binary images, but there are different approaches to calculating values in the RGB color space [26][27][28]. The main idea was to check whether the values obtained by the lacunarity equation can be implemented as criteria for segmentation of agricultural products' images.…”

Section: Introductionmentioning

confidence: 99%

Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products

et al. 2018

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Food processing industry is moving forward to a full automation of all processes, especially in technological line segments which represent critical control points of food safety. One of these points is color sorting by using machine vision, where inappropriate products are removed. Most important product appearance attributes are color and texture. During food processing, the product is captured by optical devices, mostly color cameras and lasers. The aim of this paper is to investigate new eligibility criteria for digital image segmentation by using only image from the camera. The goal is to describe the texture of the product, based on chosen mathematical measures, and to allow for recognition and then classification according to the predefined range of values in an appropriate class. Images of frozen raspberry were used. Image analysis of color parameters in RGB color space and statistical tests to examine normality of data were carried out. Thereafter, one-way Anova and correlation analysis was performed. Statistically significant difference was found for the values of two indicators: entropy and new criteria were derived from standard deviation, as well as mean values of pixels for every channel, and marked as L. After determining the range of these criteria, a new algorithm was developed for image segmentation written in Matlab. One of the results of applying this algorithm is that more than 80% of good products were recognized.

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Coke optical texture as the fractal object

Cited by 14 publications

References 17 publications

Formation of Metallurgical Coke within Minutes through Coal Densification and Microwave Energy

Formation of Metallurgical Coke within Minutes through Coal Densification and Microwave Energy

Novel Thermal and Microscopic Techniques To Determine the Causes of Suboptimal Combustion Performance at Colombian Stoker Furnaces

Application of Statistical Indicators for Digital Image Analysis and Segmentation in Sorting of Agriculture Products

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