Modeling of iron ore pelletization using 3**(k-p) factorial design of experiments and polynomial surface regression methodology

Thella, John Samuel and Venugopal, R. (2011) Modeling of iron ore pelletization using 3**(k-p) factorial design of experiments and polynomial surface regression methodology. Powder Technology, 211 1: 54-59. doi:10.1016/j.powtec.2011.03.027


Author Thella, John Samuel
Venugopal, R.
Title Modeling of iron ore pelletization using 3**(k-p) factorial design of experiments and polynomial surface regression methodology
Journal name Powder Technology   Check publisher's open access policy
ISSN 0032-5910
1873-328X
Publication date 2011-07
Sub-type Article (original research)
DOI 10.1016/j.powtec.2011.03.027
Open Access Status
Volume 211
Issue 1
Start page 54
End page 59
Total pages 6
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Abstract The process of size enlargement or agglomeration finds a variety of applications in material processing and utilization. Pelletization is one such process which uses water as medium and revolving units (Disc/Drums) to form spherical pellets from fine particulates. Green or wet pelletization is the first step in pelletization process and is of critical importance since the effectiveness of the subsequent stages of drying and in duration depends on the quality and quantity of green pellets. This research presents the work carried out to develop model equations to predict the size distribution of pellets at any given level of intervals. Modeling of pelletization was oriented towards predicting the size distribution of pellets at any given level of variables. The prediction of pellet size distribution involves quantification of the self preserving curve and correlation between D 50 and the variables. A new model has been developed to predict the size distribution of the pellets using advanced statistical software "STATISTICA". The equation Y=-0.3757X 2+1.6256X-0.74 where "Y" is the cumulative wt.% passing and "X" is D/D 50 was used to predict the pellet size distribution. Correlation between D 50 and variables was given by "D 50"=4.226+(3.106*M)-(0.544*M 2)+(2.044*I)-(0.644*I 2)+(0.2444*T)-(0.028*T 2)-(0.058*M*I)+(0.0917*I*T) using quadratic response surface methodology. The mean pellet diameter "D 50" observed versus predicted was compared. A polynomial regression equation was used to quantify the characteristic curve of iron ore slimes agglomeration process. This can be utilized to predict the complete agglomerate size distribution irrespective of the operating conditions and the size of the pelletizer if a relationship such as agglomerate median product size D 50, as a function of the operating conditions is made available.
Keyword Iron ore slimes
Modeling of pelletization
Pelletization
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Julius Kruttschnitt Mineral Research Centre Publications
 
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Created: Mon, 01 Dec 2014, 13:57:05 EST by Karen Holtham on behalf of Julius Kruttschnitt Mineral Research Centre