Published November 1, 2019 | Version v1
Journal article

A modified mathematical model for end-point carbon prediction of BOF based on off-gas analysis

  • 1. State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing (China)
  • 2. Xinyu Iron and Steel Group Co., Ltd., Jiangxi (China)
  • 3. Western Superconducting Technologies Co., Ltd., Xi'an (China)

Description

Several models for end-point carbon prediction of BOF(Basic Oxygen Furnace) based on off-gas analysis were studied in this paper. The advantages and disadvantages of the integral model, the exponential decay model and the cubic fitting model were analyzed respectively. Based on analysis of the characteristics of the decarburization rate curve, a new exponential model was established by the introduction of a correction algorithm. The principle of the proposed model involves applying the decarburization rate curve and the descending gradient of the historical heats to obtain the average decarburization curve and reference decarburization efficiency coefficient using the regression fitting method. According to the deviation between the actual and the predicted decarburization curves, the decarburization efficiency coefficient was corrected to improve the prediction accuracy. Plant trials were carried out in a 210 t converter to compare the performance of the mentioned models. The results showed that the new model exhibited better adaptability and higher accuracy than the other ones. The hit ratio of the new model reached more than 90% for the prediction of end-point carbon content within a tolerance of ±0.02%. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/668/1/012014

Additional details

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
668
Journal Issue
1
Journal Page Range
[10 p.]
ISSN
1757-899X

Conference

Title
1. International Conference on Metals and Alloys
Dates
19-22 Aug 2019
Place
Beijing (China)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54076012
Subject category
S74: ATOMIC AND MOLECULAR PHYSICS;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ACCURACY; ALGORITHMS; CARBON; MATHEMATICAL MODELS; OXYGEN; PERFORMANCE
Descriptors DEC
ELEMENTS; MATHEMATICAL LOGIC; NONMETALS