Effect of coke rate and basicity on computed tomography-measured pore parameters and effective thermal conductivity of iron ore sinter
Source abstract
Abstract
During iron ore sintering structural transformation occurs as liquid melt is formed in flame front. This study aimed to compare differences in X-ray computed tomography (XCT) measured pore parameters, and examine relationships between pore parameters and sinter effective thermal conductivity based on actual structure. Nine sinter samples (three coke rates multiply three basicity levels) were carefully prepared from pilot-scale sinter pot tests and scanned by XCT with the resolution ratio of 40 μm. The results demonstrate that higher coke rate and basicity promote melt formation during sintering, transforming sinter from particulate structure to melt-bonded structure. Under the tested conditions, sinter porosity is in the range of 36.3% ∼56.3% and its effective thermal conductivity decreases from 1.276 W/mK to 0.597 W/mK correspondingly. The anisotropic porous structure of sinter leads to different heat conduction and complicated temperature field in three spatial directions. Of all the XCT-measured pore parameters, porosity and number of +1 mm pores generally decrease with the increasing basicity at the same coke rate. The sinter effective thermal conductivity could be negatively correlated to porosity and number of +1 mm pores while there are no clear correlations with parameters including mean pore area and area of the largest pore. The statistic analysis confirms that pores in sinter could be divided into different groups to distinguish their behavior. The pores larger than 1 mm, namely macropores, contribute more than 90% to the total pore volume and set up the main orientation of pore network, determining the sinter thermal behavior predominantly.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Iron and Steelmaking Processes · Mineral Processing and Grinding · Advanced materials and composites
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (31)
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