Iron Ore Processing Improvements through Process Modeling and Computer Simulation

2001-06-15
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Title

Iron Ore Processing Improvements through Process Modeling and Computer Simulation

Published Date

2001-06-15

Publisher

University of Minnesota Duluth

Type

Technical Report

Abstract

In 1997, under the auspices of the Iron Ore Cooperative Research Program, iron ore mining companies operating on the Iron Range decided to work as a consortium in establishing expertise in the development of math models of individual taconite concentration operations and their use to simulate portions of the integrated concentration process. This led to the establishment in 1998 of the Concentrator Modeling Center within the Coleraine Minerals Research Laboratory (CMRL) of the University of Minnesota - Duluth. Following discussions on the type of software to be used by the Center, Usim Pac, mineral processing software developed by BRGM of France was selected due to the availability of a larger number of models, and model incorporation capability to add those to be developed in the future. The Center became fully operational when Dr. Salih Ersayin started to work as the program director on Nov. 1, 1999. While the application of modeling and simulation has provided significant benefits in the processing of base metal ores, its application to the processing of magnetic taconite has been hindered. This was caused by the need to incorporate the modeling of mineral liberation into the comminution models for size reduction steps, which occur between several stages of magnetic separation. An initial effort at integrating the modeling of size reduction, mineral liberation was carried out by Wiegel1 for the Erie Mining Company process in 1976. Plant scale implementation of the combined use process modeling and plant testing was reported for the National Steel Company secondary grinding section modifications 2 . Recently, Schneider 3 developed a mineral liberation model based on liberation characterization by scanning electron microscopy measurements. He validated his model using plant data obtained from the Fairlane Plant of Eveleth Taconite. For simulation purposes, he integrated his liberation approach into a ball mill grinding model. He also presented magnetic separator and hydrocyclone model structures compatible with the type of data produced by the liberation model. Despite of these developments, there still was a need to develop a simplified approach to the integrated size reduction/liberation model for taconite processing, models for magnetic separators, hydroseparators and fine screens, which would take into account the significant operating and design parameters. Therefore, the initial efforts of the Center were concentrated on development of simplified integrated mineral liberation/size reduction and magnetic separator models using funds allocated by the Permanent University Trust Fund (PUF), while providing a simulation service to taconite plant operators with the available software. Data from four plants in the Range taken as a part of an earlier Iron Ore Coop project was analyzed using the existing capabilities of the software. The data was first mass balanced and performance of individual pieces of equipment was examined. Results were presented to the plant engineers; their implications and potential improvements were discussed. To illustrate the capabilities of the software and potential benefits from the use of simulation, some modifications in plant flow sheets and operating/design conditions were simulated using the same data as a basis. These simulation results were also presented to the relevant engineers.

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Project #5600114

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NRRI Technical Report;NRRI/TR-2001/20
CMRL Technical Report;CMRL/TR-01-09

Funding information

Iron Ore Coop; University of Minnesota Duluth, Natural Resources Research Institute, 5013 Miller Trunk Highway, Duluth, MN 55811-1442; Coleraine Minerals Research Laboratory, One Gayley Avenue, Box 188, Coleraine, MN 55722

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Project #5600114

Suggested citation

Ersayin, Salih. (2001). Iron Ore Processing Improvements through Process Modeling and Computer Simulation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/188406.

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