Preventing dust formation from pellet abrasion

Bales, Axel; Ivanov, N. S.; Kulagin, I. A.; Karpov, V. V.; Семенов, А. А.

doi:10.1007/bf01140957

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The PM 10 values were calculated using the total quantity of fines generated and their aerodynamic size distributions, which were estimated using Eq. 2 1/2 p ap a ρ dd ρ (2) where d a is the aerodynamic diameter, d p is the particle diameter (from the measured size distributions), ρ a is aerodynamic density, and ρ p is particle density (determined via…”

Section: Abrasion Index Vs Dustiness Of Laboratory-made Pelletsmentioning

confidence: 99%

A New On-Line Method for Predicting Iron Ore Pellet Quality

Halt

Silva

Kawatra

2015

Mineral Processing and Extractive Metallurgy Review

View full text Add to dashboard Cite

The Abrasion Index (AI) describes fines generation from iron ore pellets, and is one of the most common indicators of pellet quality. In a typical pellet plant, dust is generated during the process and then captured. Can the dust be measured and used to predict AI?In this paper, the feasibility of using airborne dust measurements as an indicator of AI is investigated through laboratory tests and using data from a pellet plant. Bentonite clay, polyacrylamide and pre-gelled cornstarch contents and induration temperature were adjusted to control the abrasion resistance of laboratory iron ore pellets. AI were observed to range from approximately 1-12 percent. Size distributions of the abrasion progeny were measured and used to estimate quantities of PM 10 (particulate matter with aerodynamic diameter less than 10 µm) produced during abrasion. A very good correlation between AI and PM 10 (R 2 = 0.90) was observed using the laboratory pellets.Similarly, a correlation was observed between AI and PM measured in the screening chimney at a straight-grate pelletization plant in Brazil, with an R 2 value of 0.65. Thus, the laboratory and industry data suggest that measuring dust generation from fired pellets may be an effective on-line measurement of pellet quality. The data also showed that particulate emissions from pelletization plants may be directly affected by AI.

show abstract

Section: Abrasion Index Vs Dustiness Of Laboratory-made Pelletsmentioning

confidence: 99%

A New On-Line Method for Predicting Iron Ore Pellet Quality

Halt

Silva

Kawatra

2015

Mineral Processing and Extractive Metallurgy Review

View full text Add to dashboard Cite

show abstract

“…Bitumen and polymer coatings have been added to fired pellets to reduce friability and abrasion losses(Bales et al, 1986; Hey et al, 2008;Alves et al, 2014;Araujo et al, 2016). They help smoothen surfaces by covering surface asperities, and make surfaces hygroscopic which helps to retain water (meaning less water is required for suppression purposes).Cement, limestone, dolomite, alumina, and bentonite coatings have been added to direct reduction (DR) pellets to stop pellets from sticking together and forming large clusters in the DR furnace(Basdag and Arol, 2002;Hayashi, et al, 1993;Hooey, et al, 2004;Poveromo, 2006;Yi et al, 2014;Wong et al, 1999).…”

mentioning

confidence: 99%

Controlling Properties of Agglomerates for Chemical Processes

Halt¹

View full text Add to dashboard Cite

Preventing dust formation from pellet abrasion

Cited by 2 publications

References 0 publications

A New On-Line Method for Predicting Iron Ore Pellet Quality

A New On-Line Method for Predicting Iron Ore Pellet Quality

Controlling Properties of Agglomerates for Chemical Processes

Contact Info

Product

Resources

About