Shape Characterization of Ferrous Burden Material of Blast Furnace Feed using Image Analysis
Arijit Chakrabarty, Aman Tripathi, Vimod Kumar, Anurag Tripathi, Arpit Agarwal, Vishwaraj Singh, Saprativ Basu, Samik Nag

TL;DR
This paper uses image analysis to characterize the shape of blast furnace feed particles, identifying key shape descriptors and their distributions across different particle types and sizes, with implications for modeling and process optimization.
Contribution
It introduces a comprehensive method to quantify shape descriptors of blast furnace feed particles, including a novel descriptor relevant for Discrete Element Method simulations.
Findings
Shape descriptors are consistent across size ranges for each material.
Three key shape descriptors effectively characterize particle shapes.
The new contact eccentricity descriptor is highly relevant for granular material simulations.
Abstract
In this study, we attempt to characterize the shape of three different types of grains commonly used in the iron and steel-making industry, namely pellet, sinter and iron ore lump. We choose particles over the entire size ranges used in industrial-scale blast furnace and consider two different size ranges of pellet particles and four different size ranges for sinter and iron ore lumps. We perform image analysis to calculate size and shape-related properties of the grains. We select some of the common length scales used to measure the size of the particles and categorize them in different classes. We show that the length scales of a particular category class are well correlated with each other. We identify the independent, uncorrelated length scales for the particles from different categories. Using these uncorrelated length scales, we define different shape descriptors and obtain the…
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Taxonomy
TopicsIron and Steelmaking Processes · Mineral Processing and Grinding · Granular flow and fluidized beds
