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Exploring the capability of muon scattering tomography for imaging the components in the blast furnace
RISE - Research Institutes of Sweden, Swerea, Swerea MEFOS.
RISE - Research Institutes of Sweden, Swerea, Swerea MEFOS. Luleå University of Technology, Luleå.
LKAB R&D, Sweden .
LKAB R&D, Sweden ; Luleå University of Technology, Sweden.
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2018 (English)In: ISIJ International, ISSN 0915-1559, E-ISSN 1347-5460, Vol. 58, no 1, p. 35-42Article in journal (Refereed) Published
Abstract [en]

Knowing the distribution of the materials in the blast furnace (BF) is believed to be of great interest for BF operation and process optimization. In this paper calibration samples (ferrous pellets and coke) and samples from LKAB’s experimental blast furnace (probe samples, excavation samples and core-drilling samples) were measured by the muon scattering tomography detector to explore the capability of using the muon scattering tomography to image the components in the blast furnace. The experimental results show that it is possible to use this technique to discriminate the ferrous pellets from the coke and it is also shown that the measured linear scattering densities (LSD) linearly correlate with the bulk densities of the measured materials. By applying the Stovall’s model a correlation among the LSD values, the bulk densities and the components of the materials in the probe samples and excavation samples was established. The theoretical analysis indicates that it is potential to use the present muon scattering tomography technique to image the components in various zones of the blast furnace.

Place, publisher, year, edition, pages
2018. Vol. 58, no 1, p. 35-42
Keywords [en]
Blast furnace, Bulk density, Muon scattering tomography, Charged particles, Coke, Excavation, Iron, Optimization, Pelletizing, Probes, Tomography, Calibration samples, Experimental blast furnaces, S models, Scattering density, Blast furnaces
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-33256DOI: 10.2355/isijinternational.ISIJINT-2017-384Scopus ID: 2-s2.0-85040724568OAI: oai:DiVA.org:ri-33256DiVA, id: diva2:1182177
Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-03-16Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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