BOF Cold Model: Mixing time study at multiphase conditions
Research output: Thesis › Doctoral Thesis
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2021.
Research output: Thesis › Doctoral Thesis
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TY - BOOK
T1 - BOF Cold Model
T2 - Mixing time study at multiphase conditions
AU - Godinho de Carvalho, Daniel Augusto
N1 - no embargo
PY - 2021
Y1 - 2021
N2 - The BOF process was born in 1949 in Linz, Austria. Fast growth for the Basic Oxygen Processes (BOP) was observed in the 1960s. By 1971, Basic Oxygen Furnace (BOF) produced more than half of the world's steel. The LD process led worldwide steel production to increase from 0.2 to 1.8 billion metric tons of crude steel per year. The integrated steelmaking route based on the BF-BOF is directly responsible for 70% of total world steel production. At least up until 2050, primary steelmaking based on the BOF technology is assumed to continue the main process route. In an earlier work about lime dissolution and slag making for an industrial 330t BOF, the same process as presented in this thesis, several process parameters were studied. Nevertheless, the model's weak point was the efficiency factors that correlate the mixing energy related to top lance, bottom stirring, and decarburization reactions. A couple of different reports for the agitation of a top blowing jet to the bath and bottom stirring are available in the literature, and different expressions to calculate the agitation power have been proposed. Although experimental conditions are used, these empirical assumptions are not necessarily suitable for all BOF processes. Those parameters substantially impact the steel process productivity, costs, and quality, and the mixing time concept investigated through cold modelling is perfect for assessing the system performance. This thesis developed investigations through laboratory cold model to improve the mixing time and mass transfer rate due to a gradient of apparent density caused by different bottom stirring flow zone. The proposed setups were validated in the industrial environment, and more than 1750 trial heats were produced in a 330t BOF. This research introduced novel modified dimensionless numbers, the new parameters added in the equations delivered a unique solution to develop a complete BOF process similarity. For the first time, a similarity study employed and associated the effects of the multi-nozzle supersonic lance, slag-phase and the bottom stirring gas parameters to design a new BOF cold model. The methods applied in the laboratory measurements employed a mix of modified procedures available in the literature, and new techniques to evaluate the bath mixing time, mass transfer rate, jet penetration, decarburization area, sloping and projection rate for BOF cold modelling. The industrial-scale experiments were fundamental to validate the laboratory trials, the first phase of experiments delivered important laboratory and process data for seven different bottom stirring configurations. Despite the influence of many other parameters and variables faced in the industrial environment, the performed trials delivered essential process data for a statistical and machine learning analysis.
AB - The BOF process was born in 1949 in Linz, Austria. Fast growth for the Basic Oxygen Processes (BOP) was observed in the 1960s. By 1971, Basic Oxygen Furnace (BOF) produced more than half of the world's steel. The LD process led worldwide steel production to increase from 0.2 to 1.8 billion metric tons of crude steel per year. The integrated steelmaking route based on the BF-BOF is directly responsible for 70% of total world steel production. At least up until 2050, primary steelmaking based on the BOF technology is assumed to continue the main process route. In an earlier work about lime dissolution and slag making for an industrial 330t BOF, the same process as presented in this thesis, several process parameters were studied. Nevertheless, the model's weak point was the efficiency factors that correlate the mixing energy related to top lance, bottom stirring, and decarburization reactions. A couple of different reports for the agitation of a top blowing jet to the bath and bottom stirring are available in the literature, and different expressions to calculate the agitation power have been proposed. Although experimental conditions are used, these empirical assumptions are not necessarily suitable for all BOF processes. Those parameters substantially impact the steel process productivity, costs, and quality, and the mixing time concept investigated through cold modelling is perfect for assessing the system performance. This thesis developed investigations through laboratory cold model to improve the mixing time and mass transfer rate due to a gradient of apparent density caused by different bottom stirring flow zone. The proposed setups were validated in the industrial environment, and more than 1750 trial heats were produced in a 330t BOF. This research introduced novel modified dimensionless numbers, the new parameters added in the equations delivered a unique solution to develop a complete BOF process similarity. For the first time, a similarity study employed and associated the effects of the multi-nozzle supersonic lance, slag-phase and the bottom stirring gas parameters to design a new BOF cold model. The methods applied in the laboratory measurements employed a mix of modified procedures available in the literature, and new techniques to evaluate the bath mixing time, mass transfer rate, jet penetration, decarburization area, sloping and projection rate for BOF cold modelling. The industrial-scale experiments were fundamental to validate the laboratory trials, the first phase of experiments delivered important laboratory and process data for seven different bottom stirring configurations. Despite the influence of many other parameters and variables faced in the industrial environment, the performed trials delivered essential process data for a statistical and machine learning analysis.
KW - BOF
KW - Converter
KW - LD
KW - Cold Model
KW - Mixing Time
KW - Mass Transfer Rate
KW - Mixing Energy
KW - Industrial
KW - Laboratory
KW - Machine Learning
KW - Decarburization Area
KW - Jet Penetration
KW - Bottom Stirring
KW - Similarity
KW - Dimensionless Numbers
KW - Sauerstoffkonverter
KW - LD Konverter
KW - Kaltmodell
KW - Vermischungszeit
KW - Stofftransportrate
KW - Vermischungsenergie
KW - Industrie
KW - Labor
KW - Maschinenlernen
KW - Entkohlungsfl�che
KW - Strahleindringung
KW - Bodensp�len
KW - �hnlichkeit
KW - dimensionslose Zahlen
M3 - Doctoral Thesis
ER -