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March 2007
Vol. 4, No. 3
Pre-Show Issue for AISTech 1007 plus Iron Production Technologies

About the Cover

DRI Technology and Process Development at Mittal Steel Co.
Ali Farhadi (left), George Tsvik (right), Israel Hernandez and Uwe Braun, Mittal Steel Co., East Chicago, Ind. (ali.farhadi@mittalsteel.com, george.tsvik@mittalsteel.com, israel.hernandez@mittalsteel.com, uwe.braun@mittalsteel.com)

Mittal Steel’s implementation of such technologies as pellet coating, oxygen injection and high bustle gas temperature have required special calculations, models and tests. These and other developments at the company’s DRI plants are described.

Sulfur Filtration Improvements at Dofasco’s No. 1 Byproducts Plant
Zlatko Taravski (left), Phil A. Roppel (center) and John D. Nicholls (right), Dofasco Inc., Hamilton, Ont., Canada (zlatko_taravski@dofasco.ca, john_nicholls@dofasco.ca, philip_roppel@dofasco.ca)

Reliable, continuous sulfur removal when cleaning coke oven gas can be achieved with an automated diaphragm pressure filter. This paper details the procurement, installation and commissioning of the filter and the construction of facilities to house the new equipment.

Three-dimensional CFD Analysis for Blast Furnace Hearth Wear
David Roldan, project engineer, Electro-Motive Diesel Inc., LaGrange, Ill.; Yu Zhang (top left), research associate, Rohit Deshpande (top right), graduate student, and Chenn Q. Zhou (bottom left), professor and head, Purdue University Calumet, Department of Mechanical Engineering, Hammond, Ind. (qzhou@calumet.purdue.edu); D. (Frank) Huang (bottom center), staff engineer, and Pinakin Chaubal (bottom right), director of process research, Mittal Steel USA Research and Development Center, East Chicago, Ind. (pinakin.chaubal@mittalsteel.com)

A three-dimensional CFD model, including both hot metal flow and heat transfer, was developed to analyze the hearth wear of blast furnaces based on detailed temperature records for different time periods. The effects of operating conditions on hearth wear are also discussed.

Blast Furnace Optimization — The Next Generation
Johann Hörl, Martin Schaler and Klaus Stohl (pictured), head of projects and spares — Linz, Siemens VAI Metals Technologies GmbH & Co., Linz, Austria (klaus.stohl@siemens.com); Ismo Piirainen and Olaus Ritamäki, VAI Finland Oy, Oulu, Finland (olaus.ritamaki@siemens.com)

This paper highlights the results from selected installations of two expert systems to support blast furnace operation. The structure and features of the new, combined system, VAiron TNG, are explained in detail.

Modular Cast Block — The Future of Coke Oven Repairs
Robert A. Bloom and Paul A. Saffrin (pictured), Vanocur Refractories LLC, Tonawanda, N.Y. (paulsaffrin@yahoo.com)

A modular repair system was developed that cuts coke oven repair time and costs in half compared to traditional silica repairs. This paper discusses the development of the system and its successful application.

Controlling Blast Furnace Pulverized Coal Injection to Increase PCI Rates
Roland Weiser, Ingo Braune and Peter Matthes, AMEPA GmbH, Aachen, Germany (info@amepa.de)

This paper reviews the benefits of real-time control of pulverized coal injection in a blast furnace through closed-loop processes. Practical examples are reviewed, showing how furnace operating stability can be maintained while increasing injection rates and lowering overall production costs.

Report on the Longitudinal Charpy V-Notch Model
Brian Gee, quality and safety manager, Primary Steel LLC, Oakland, Calif. (bgee@primarysteel.com)

A linear regression model predicting whether a carbon steel plate would pass a Charpy impact test has been developed. This was done to prevent testing material that would not pass the required Charpy test, without having to sample the plate for grain size. Avoiding testing plates that would not pass would preclude loss of material and time, resulting in savings for the company. The model does not require metallographic sampling to preclude lost material and delays in processing of orders.

The Charpy LCVN model is statistically robust for ASTM A36, A516 Gr70 and A572 Gr50. The model agrees with metallurgical theory. C and Mo show a strong influence on Charpy impact properties. When impurities (sulfur and phosphorus) are too high, the chance of obtaining satisfactory test results would diminish. This is more evident when testing at lower temperatures. To account for grain size, the ratio of yield strength (YS) to ultimate tensile strength (UTS), and the percent elongation were incorporated into the model.
This paper records the development process and theory for the LCVN model. The first part of the paper describes the Charpy impact test and the metallurgical theory involved. The second part of the paper discusses the regression analysis used to develop the model.