Ironmaking & Steelmaking: Processes,Products and Applications

The continuous casting (CC) mould may appear very peaceful when viewed from above, but the powder bed hides relentless fluctuations in the following phenomena: metal flow, thermal gradients, chemical reactions and multiple phase transformations. When observed separately, some of these phenomena seem to have a ‘simple behaviour’, which may appear easy to control through the main casting parameters (e.g. casting speed, pouring temperature and powder type) and associated control systems (e.g. mould level control, automatic powder feeding and mould oscillation). However, when combined, these phenomena exhibit periodic fluctuations in behaviour, which is both difficult to predict and control. For instance, the combination of casting speed, submerged entry nozzle design and slab size can cause the metal flow pattern to shift from double roll to single roll and back, which can cause unstable fluctuations in metal level, standing waves, etc. In this respect, the CC process closely resembles a meteorological system where both variations and local fluctuations in temperature, humidity, pressure, etc., can result in effects that are difficult to predict in the long term. This is equivalent to the famous Lorenz premise: ‘Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?’ In this paper, we give some examples of the ‘butterfly effect’ in CC discussed below by using a mathematical model able to predict the slab solidification inside the mould in which various factors affecting the process stability are analysed and the probable sources of fluctuation are identified.

The automotive industry is changing with ever increasing speed. The current economic and environmental pressures mean that the vehicles of tomorrow will be very different to those we drive today. As new technologies are developed to enable these changes, the materials industry must respond quickly to ensure that they are both manufacturable and cost effective, as well as deliver the performance required to drive the industry forward. This article aims to identify the key technology developments, the challenges that they face and how Tata Steel is helping to overcome them.

The Worldsteel Water Management Project was initiated in June 2007 with the aim to prepare steel plants for future public and political pressures relating to water. Following several meetings and a presurvey, a water management survey was launched in July 2009. Data were received from 29 steel plants, representing 8% or approximately 111 million tonnes of the world’s total steel output in 2008. Results show that water consumption (consumption within this article refers to: intake water, when a complete steelworks is in question and to actual water needed by the process or facility (intake+reuse water) when talking at process level) at the steel plants varies from under 1–150 cubic metres per tonne of steel (m³ ts⁻¹) produced. The volume and quality of consumed and discharged water relate to steel plant configuration, geographical location and local legislation. Nearly 82% of all the water is used for once-through cooling. The data collected on for example, waste water treatment technologies and discharge quality are available in a digital database that can be used for, as an example, optimising water management within processes. This paper is based largely on the Worldsteel report ‘Water Management in Steel Industry 2011’ and outlines finding of the Water Management Working Group.

A steel mill is a large logistical hub, with raw materials and energy as input and steel plus some other materials as output. The vocabulary to designate the latter is fuzzy and changing, and it depends on who speaks about them: co-products, byproducts, residues, waste, emissions, pollutants, discharge, etc., are used in different contexts. This profusion of names echoes the conceptual hurdles that block the way when numbers have to be attributed to the co-products, related to either environmental footprints or economic values, especially if both are mixed. The paper focuses on the example of blast furnace slag, which is sold to the cement industry in large quantities as a substitute to clinker. The practice is a lively example of an industrial ecology synergy between two economic sectors: both sectors, collectively, decrease their environmental footprints in terms of energy consumption, greenhouse gas emissions, resource depletion, etc., in an unambiguous way. Many issues arise, however, when exact figures have to be worked out to allocate a footprint to each partner in the synergy. Life cycle assessment seems like a good candidate to do that job, but from a practical standpoint, the method can be implemented in so many versions and flavours that the answers end up in a series of very different figures, which confuse rather than clarify the issue. What is argued here is that these difficulties are due to the fact that the underlying problems are not yet solved, and that it is naive to ask a technology like life cycle assessment to solve issues related to the allocation of the cost of the climate change externality to commodity materials like cement and steel. Unsolved problems are due to the uncertainties related to this process. Until these issues are cleared, it is proposed either to focus mainly on the synergistic benefits of the cooperation between the two sectors or to accept different estimates of the footprint of the co-products in the two sectors. This example is a typical case in point related to what we have called the collision between the ecosphere and the anthroposphere.

Modelling the transport phenomena in tundishes has been a vast area of research for the last three decades. Many papers have been published and are available in the literature on this subject. The basics of modelling involve a similarity criterion between the model and the full scale prototype and are well documented in major textbooks. However, the similarity criteria are different for different cases. For example, for fluid flow in a tundish, the Re and Fr similarity is considered, whereas for heat transfer, the Pr and Pe number similarity should be considered. Numerous other examples can be cited. It is really important to know which similarity criteria should be used for a particular case. In this paper, a new dimensionless number Gu has been proposed when dealing with the modelling of inclusions separating out in a tundish. All dimensionless numbers can be represented as a ratio of two characteristic time scales, and this fact is highlighted in the present paper.

Improving steelmaking and casting processes to adapt to the requirements of internal and external customers involves continuous monitoring and evaluation of existing and development of new steel refining practices. Internal quality control of semifinished products requires tools that can correlate product defects to process anomalies. This article focuses on use of techniques such as measurement of complete steel and slag chemistry, inclusion analysis, process analysis and thermodynamics to assess the influence of process conditions on product properties. Examples from both long and flat products, including low carbon aluminium killed steels, medium carbon aluminium killed steels, advanced high strength steels and free machining steels, are presented to explain the benefit of using these tools to understand the process conditions necessary for clean steelmaking and thus improve product quality.

Mathematical modelling of both fluidised and packed bed reactors has been carried out. In the fluidised bed reactor, a two-phase bubbling bed model has been used in order to estimate the interaction between gas bubbles and the dense phase in the bed. Modelling in the packed bed reactor was carried out based on that used by Ranade and Evans. The reduction behaviour of solid reactants has been expressed by the grain model, and computerised programs were developed in MATLAB software for solving the governing equations at conditions of different temperatures and pressures. The behaviour of both types of reactors for variations in temperatures, size of the pellets and inlet gas compositions has been studied, and a comparison between the reactors has been carried out. Excellent mixing of reactants in the fluidised bed helps to minimise temperature variations and renders this system attractive for carrying out gas–solid reactions. The fluidised bed reactors show better conversion of reactants in comparison with packed beds when solid reactants are used in the form of small pellets.