Ironmaking & Steelmaking: Processes,Products and Applications

In iron ore sintering, granule deformation and compaction can be responsible for significant losses in bed voidage and green bed permeability. In this study, uniaxial compression tests have been used to examine the bed strength of granulated single and binary iron ore sinter mixes. The results show that at low moistures, bed strength is dependent on the granule layer mass to nuclei mass ratio. For binary iron ore sinter mixes, bed strength was found to increase as levels of Channel Iron ore were increased. Permeability–moisture curves for a series of single ore sinter mixes were recorded to examine the key parameters that affect this relationship. The results confirmed that the porosity of the ore pore size distribution and contact angle all affect the shape or width of the curves and the moisture at maximum permeability. The height of the curves is determined by bed voidage and the granule size distribution. This study has demonstrated that provided sufficient water is available during granulation, both Channel Iron and Marra Mamba ores granulate well, forming packed beds with permeability and strength comparable with or higher than those formed from less porous Brockman and Itabirite ores.

A prerequisite of a smooth operation of the ironmaking blast furnace is that the quality of the burden is stable. In blast furnaces where sinter is used as the (main) iron bearing material, its quality plays a crucial role in productivity and fuel economy. Simultaneously the corresponding factors must be considered for the sinter plant. The present paper studies the influence of three variables characterising the bedding piles and five sinter plant operation variables on sinter quality, sinter plant productivity, specific fuel consumption and share of cold return fines. Daily mean values for a period of five years of operation were used in the data driven modelling based on feedforward neural networks. The resulting models were found to describe the major changes in the outputs well. The input–output relations captured by the models were analysed by perturbing one input variable of the networks at a time and analysing the predicted behaviour of the outputs.

For the production of synthesis gas utilised in Midrex direct reduction plants, catalytic steam/CO₂ hydrocarbon reforming in tubular reformer is the major process. Owing to the high heat input through the Midrex reformer tube wall, the endothermic nature of reforming reactions, low mass velocity of feed gas and large tube diameter, the catalyst bed is exposed to considerable axial and radial temperature gradients. These radial concentration and temperature gradients may create local areas with potential for carbon formation. To investigate this phenomenon, a rigorous two-dimensional model is developed for simulating the operation of a Midrex reformer which applies a dual catalyst loading profile. Both process side and furnace side have been included in this integrated model. Simulation results are in good agreement with available data from an actual plant. Using this model, a thermodynamic approach is applied to recognise zones in which the risk of carbon formation is high inside the reformer tubes. The results show that the first half of tubes, both in centre and near the wall, is critical from carbon forming point of view. Furthermore, the model shows that how a certain catalyst loading profile will affect the operation of the reformer.

Thermal conductivities of CaO–SiO₂–Al₂O₃ glassy slags have been determined using the nonstationary hot wire method as functions of (mol.-%Al₂O₃)/(mol.-%CaO) and (mol.-%SiO₂)/(mol-%Al₂O₃) ratios over a temperature range 300–1270 K. The thermal conductivities of the samples investigated were in the range between 1·0 and 1·6 W m⁻¹ K⁻¹. The thermal conductivities of samples having a constant concentration of SiO₂ increased with increasing the (mol.-%Al₂O₃)/(mol.-%CaO) ratio as long as the constant pressure heat capacity per unit volume was kept constant. This increase in thermal conductivities would be due to increases in the speed of sound and/or the phonon mean free path by re-polymerisation of the network structure of silicate glasses by Al₂O₃. On the other hand, the thermal conductivities of samples having a constant value of NBO/T (the ratio of the number of non-bridging oxygen ions per tetrahedrally coordinated cation) decreased with increasing the (mol.-%SiO₂)/(mol.-%Al₂O₃) ratio. This decrease in thermal conductivities would be dominated by the constant pressure heat capacities per unit volume of the samples.

The focus of the present work was to examine whether vanadium rich phase(s) could be obtained in converter slags having high V₂O₅ contents. Slags from SSAB Oxelösund, Sweden and Ma Steel, China were studied. Despite of the composition difference, slags from both industries were found to contain essentially the same phases after heat treatment. No vanadium rich phase could be obtained by only heat treatment of the slag. The addition of 12 mass%SiO₂ changed substantially the phase relationships in the slags. Two vanadium rich phases were detected in the slag samples with SiO₂ addition. One of the phases was expected to be a solid solution of 3CaO.V₂O₅ and 3CaO.P₂O₅ with, <3 mass%SiO₂ dissolved. The other vanadium rich phase had high SiO₂ content. About 67–68 mass% vanadium was captured by the vanadium rich phase(s) after the treatment. The present finding would open up new opportunities for recovery of vanadium from converter slags.

The friction between mould and solidifying shell has a critical influence on slab quality, casting productivity and operating safety. In the present paper, the online monitoring system of mould friction (MDF) based on power measurement is briefly described. Using plant records, MDF measured on a slab caster is used to investigate the response of MDF to abnormalities in continuous casting. The online measured data have also been employed to examine the influence of liquid steel quality, casting powder and oscillation mode on frictional behaviour. Finally, the present paper introduces recent developments of a prediction method for abnormalities using neural network models and presents several examples of simulation prediction. The analytical and simulation results lay the foundation for an intelligent mould with online detection of defects, adjustment of operational parameters, optimisation of monitoring system and even prediction of abnormalities in slab continuous casting.

Static recrystallisation kinetics during hot deformation of two microalloyed steels (C–Ti–V and C–Ti–Nb) has been quantified. Double hit compression test using a Gleeble 1500 thermomechanical simulator was conducted to determine the recrystallisation kinetics. The kinetics of static recrystallisation was found to be more sluggish in the case of microalloyed steels with niobium additions as compared with other grades of microalloyed steels. The rate of recrystallisation increases with increasing temperature, strain and strain rate. The results are compared with other grades of microalloyed steels, mainly with Ti, Ni and Cu additions, from literature. For niobium containing microalloyed steels, a higher temperature is required for recrystallisation as compared with other microalloyed steels.

The microstructure and mechanical properties of Incoloy A-286 forgings are sensitive to thermomechanical processing. In this research the hot deformation behaviour of A-286 superalloy is characterised in the temperature range of 1000–1100°C and strain rate range of 0·001–0·1 s⁻¹ using the compression tests in order to develop a correlation between the grain size and the process parameters. It is found that at a strain rate of 0·001 s⁻¹ in the temperature range of 1000–1100°C and at a strain rate of 0·01 s⁻¹ in the temperature range of 1050–1100°C, the material exhibits dynamic recrystallisation (DRX), while at a strain rate of 0·01 s⁻¹ and at the temperature of 1000°C and at a strain rate of 0·1 s⁻¹ and in the temperature range of 1000–1100°C, the alloy exhibits the dynamic recovery (DR).

A comprehensive computer based system for online prediction of mechanical properties and offline prediction of the microstructure of hot rolled C–Mn and microalloyed steel strip of has been developed. The approach used was based on two types of model: a neural model that predicts the mechanical properties and a physically based semiempirical model that predicts the microstructural features. The mechanical properties of the hot rolled strip are calculated online, but it is also possible to simulate the effects of steel composition and process parameters on the mechanical properties. The microstructural model is an offline tool for use in research and development, product planning and production. It can be applied to the study of microstructural evolution during hot rolling or to estimate changes caused by process conditions or by the steel composition. The system provides information that has not been available before, thus enabling more precise process planning, improvement of the consistency of products and better opportunities for future steel development.

A model based on an artificial neural network (ANN) has been developed for prediction of flatness of cold rolled (CR) sheet in a tandem cold rolling mill for white goods applications. Various process parameters including roll bending, roll shifting, tensions between stands etc., which affect flatness of CR sheet are considered in the model. Substantial amounts of data are obtained from level II automation of PL-TCM of TATA Steel to develop the prediction model. The developed ANN model, based on back propagation algorithm, is able to predict the flatness defects like edge buckles, centre buckles for a given set of rolling parameters. The model involves a large number of process parameters and application of ANN to such kind of problems is successfully demonstrated in the present study. The model is in good agreement with the observed flatness values at different locations across the width. High coefficient of determination close to 0·919 is achieved for the prediction of flatness at edges.

The present paper discusses the process development and optimisation conducted over a two-year period at the continuous caster at Columbus Stainless to allow an increased sequence length, thereby satisfying the continual drive for increased throughput, lower cost of production and higher quality. Increased sequence length results in longer exposure of refractory to steel or slag resulting in more erosion and chemical attack. The refractory system in use at Columbus Stainless was initially designed and optimised for 6 h of casting and the focus of the development was to increase this time to 14 h. This objective was achieved by modifications to tundish design and lining, optimisation of the tundish cover, modifications to stopper and SEN design, composition and operating practise. After these changes, the original objective of increasing the sequence length to 14 h was achieved with a concomitant saving in refractory cost per ton of up to 35%.

Cleanliness of steel is a primary requirement for flat products. It is obtained with minimum of defects by controlling the liquid flow characteristics in the mould and fluctuations over the meniscus surface. Liquid flow in the mould region is due to the momentum of the pouring stream which in turn is related to the clogging of submerged entry nozzle and argon flow in the mould. This makes control of liquid steel flow dynamics in the mould important. The mould level fluctuation index, flow fraction or clogging percentage and optimised gas flow models have been developed and are correlated for minimised surface fluctuations throughout the casting sequence. Tundish weight, casting speed, casting section and immersion depth of the nozzle which primarily change the flow profile inside the mould are the key operational variables considered for model calculations. The operational parameters were adjusted to follow the developed models criteria for different casting conditions. Online application of these operational control models contributed to stabilise the mould fluid flow and have helped in decision making for pumping, flushing and tube changing. The present paper describes the mathematical approach adopted in calculation of optimum casting parameters for controlling flow of liquid steel, nozzle clogging and gas injection rate at JSW Steel Ltd. This has resulted in considerable reduction in mould level fluctuations and production of superior quality slabs even at higher casting speeds.