Calibration of the perfect mixing model to a dry grinding mill |
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| Affiliation: | 1. Dept. of Mining, Metallurgy and Materials Engineering, Laval University, QC, Canada G1K 7P4;2. Quebec Metal Powders Ltd., Tracy, QC, Canada;1. Department of Mining Engineering, Faculty of Engineering and Architecture, Eskisehir Osmangazi University, 26480 Eskisehir, Turkey;2. Department of Biology, Faculty of Arts and Science, Eskisehir Osmangazi University, 26480 Eskisehir, Turkey;3. Department of Biotechnology and Biosafety, Graduate School of Natural and Applied Sciences, Eskisehir Osmangazi University, 26480 Eskisehir, Turkey;4. Department of Biology, Graduate School of Natural and Applied Sciences, Eskisehir Osmangazi University, 26480 Eskisehir, Turkey;5. Anadolu University, Porsuk Technical College, 26470 Eskisehir, Turkey;1. School of Materials Engineering, Purdue University, Neil Armstrong Hall of Engineering, 701 West Stadium Avenue, West Lafayette, IN 47907, USA;2. Progressive Surface, 4695 Danvers Dr. SE, Grand Rapids, MI 49512, USA;3. High Temperature Materials Laboratory, Oak Ridge National Laboratory, Building 4515, 1 Bethel Valley Rd, Oak Ridge, TN 37831, USA;1. Isotope Production and Applications Division, Bhabha Atomic Research Centre, Mumbai 400085, India;2. Chemical Engineering Division, Bhabha Atomic Research Centre, Mumbai 400085, India;3. Mineral Processing Division, Bhabha Atomic Research Centre, Mumbai 400085, India |
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| Abstract: | The perfect mixing model is calibrated to a dry grinding mill used to prepare iron powder for powder metallurgy applications. The calibration procedure was modified to account for possible error on both the mill feed and discharge size distributions, while the usual calibration criterion is based on the estimation error of the mill product size distribution. The calibration criterion was also modified to allow the simultaneous processing of several sampling campaigns to estimate common appearance, breakage and discharge rate functions. Calibration results are analysed in terms of reproducibility of model estimates and model capacity to predict the mill powder content as a function of the mill throughput and power drawn. |
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