Poster Template

1
INTELLIGENT ENERGY MODEL OF STEEL FOUNDRY MELTING
OPERATIONS.
Siddhartha Biswas, Materials Science and
Engineering
Dr. Kent D. Peaslee, Materials Science and
Engineering
HEAT BALANCE IN LADLE

• OBJECTIVES
• Cost of Energy has a major share in overall
  production cost in steel foundry.
• Energy cost is increasing.
• Energy production is related to CO2 emission.
• Efficient use of energy minimizes all of the
  above.

METHODS FOR PREPARING ENERGY MODEL SPREADSHEET
INPUT
Heat accumulated by lining
-
CFD Models
Experimental Data
Theoretical Data
Spreadsheet
Neural Network
Compare calculate
FLUENT Model
OUTPUT
1000 lb alumina castable ladle
INPUT
Weight Composition of melt Temperature measurements Refractory type Energy consumption corresponding to different foundry practice Slag practice details
OUTPUT
Energy efficiency by stages of melting Options for improvement Overall efficiency
FACTORS AFFECTING TAP TEMPS / COOLING RATES

• ladle capacity is the main factor influencing
  heat losses
• Cooling rate in same capacity ladle can vary by
  up to 5X
• Holding time
• Type of lining
• Preheating temperature
• Radiation from top.

• APPROACHES
• Research wrought Industry energy usage.
• Research steel casting industry energy usage.
• Laboratory study of factors affecting energy
  consumption during melting in foundries.
• Heat balance and components of heat losses were
  analyzed using FLUENT and FACTSAGE.
• Improving Melting Efficiency through the
  application of new refractory materials.
• Industrial trials to improve energy efficiency.
• Modeling to determine areas for improvements in
  energy usage.

• FEATURES of SPREADSHEET
• User Friendly
• Suggest a to do list to improve energy efficiency
• Make predictions about effect of process
  improvements
• Calculate efficiency for current foundry practice
• Compare results with previously saved data

Comparison of required tap temperatures for aim
pour temperature and holding time in ladles with
different refractories
FUTURE WORK DEVELOP THE SPREADSHEET AND
VALIDATE THE USE OF IT THROUGH INDUSTRIAL
TRIALS.
Three Types of Lining Materials Studied

• Acknowledgements
• Intelligent Systems Center
• Steel Founders Society of America and the member
  companies that have provided support for this
  work.
• U.S. DOE Award No. DE-FC36-04G014230-Energy
  SMART(support does not constitute an endorsement
  by DOE of the views expressed).

low density magnesia
porous alumina castable
alumina castable