Control system of water flow and casting speed in continuous steel casting

The aim of this paper is to present an application of the input variable significance analysis to finding probable causes of product defects occurring in continuous casting (CC) of steel. The research was carried out using production data routinely recorded in one of Polish steel plants and basically referred to defective fraction of billets per heat as the process output. The data did not include the cases with zero defects which made the analysis difficult. The process inputs included eight parameters of different nature (physical, organizational and human). For determining which of the process input parameters are crucial for the output and which of them can be easily eliminated in further analyses two different approaches were applied and compared. The basic tool was an MLP-type Artificial Neural Network in which the relative significance was defined as the sum of the absolute weights of the connections from the given input node to all the nodes in the first hidden layer. As a complementary method the one-way analysis of variance (ANOVA) was utilized in which the value of the F-statistics is used as a measure of the input significance. It was found that the both methods indicate that the start-time of the CC process is the factor highly influencing the fraction of defective products. The process physical parameters which are expected to have a large influence on the billet quality, i.e. deviations from nominal casting temperature and deviation from nominal casting speed also appeared to be significant, moreover their variations also highly depend on the start-time of the CC process. The final conclusion is that the direct cause of the defective products are incorrect adjustments of the casting speed occurring mainly in the morning hours, however not correlated with particular operators. This finding can considerably facilitate the identification of the root cause of the defects by the plant engineers. Some recommendations concerning the future work are also given.

After investigation in many continuous casting shop of steel, a dynamic water distribution model is proposed for flexible control on secondary cooling in continuous casting. In this model, the water cooling intensity is determined by the model casting speed instead of the real casting speed. When the casting speed is steady, the model casting speed is equal to the real casting speed. When the real casting speed is changing, the model casting speed according to calculating algorithm to adjust and approaches to the real one, but there is a time delay between them, so it can avoid the slab surface temperature fluctuated due to casting speed changes. The secondary cooling can be dynamically controlled by monitoring the model casting speed. The compare of the simulation results and the measured results reveals that the temperature field and thickness of slab shell in simulations agree very well with the real production situations.

The paper analyses the effect of the nozzle arrangement on the continuous steel casting, depending on its shape and dimensions. At the same time, the work analyses the effect of cooling water pressure on the contact with the cast in order to improve the heat transfer coefficient at boiling. The present research in that, more specifically, disposed cooling water injection nozzle during the continuous casting method for arranging the nozzle for spraying cooling water to the cast surface to cool the play cast steel during the continuous casting of a continuous cooling water jetting nozzle alignment during casting It relates. An injection nozzle arrangement method during continuous casting is provided to evenly inject cooling water onto the surface of a continuous cast steel slab in a secondary cooling zone during the continuous casting.

Different parameters can be used together in the continuous casting process known as an important steel production stage in the world. It is important to use metallurgical appropriate parameters to meet the product properties. Many innovations have been made in the continuous casting process from past to present. It is known that studies are carried out on many effective topics such as steel analysis, refractory materials, continuous casting parameters, in order to make the proper solidification that will meet the needs with its continuous casting capabilities. When continuous casting parameters are examined; the casting speed parameter was found to be effective in terms of quality needs in macro samples. Therefore, in this study, the effect of the increase of casting speed parameters on the quality of macro samples was investigated. As a method; in high carbon, micro-alloyed DIN EN ISO 16120-2: 2011-C66D quality steels, in different castings, this parameter was changed and macro samples were taken and evaluated in terms of quality needs. When macro sample quality results are compared; the effect of casting speed was observed. In this study; the effect of the increase in casting speed in continuous billet casting facility on optimum metallographic and physical quality has been investigated and the results have been interpreted.

In the continuous casting of steel, mold level fluctuation caused by unsteady bulging of the solidifying shell affects the surface quality of the product and stable operation of the continuous casting process. To clarify this problem, inter-roll bulging and unsteady bulging in experimental casting machines and commercial continuous casting machines have been measured by various methods in a number of studies. In this study, the fluctuation of inter-roll bulging with time in a commercial continuous casting machine was measured by an ultrasonic range finder using a water column. In these measurements, the fluctuation of the segment was also considered. The validity of the measured data was estimated by comparison with the mold level. The results showed that both inter-roll bulging and the mold level fluctuated with the cycle calculated from the roll pitch and casting speed, and the amplitude of the mold level fluctuation converted from the amount of fluctuation of inter-roll bulging corresponded to the actual mold level fluctuation. Therefore, the cycle and absolute amount of inter-roll bulging fluctuation measured in this study were considered reasonable. These results also revealed that the value measured in this study corresponded directly to the fluctuation of inter-roll bulging as such.

To estimate the quality condition in continuously cast steel slabs, simple but accurate macrosegregation criteria have been proposed. The formation of macrosegregation phenomena in continuous casting of peritectic carbon steels has been investigated by metallographic study of collected slab samples. The metallographic study involved plant trails to collect the slab samples and to prepare them for chemical macrosegregation analysis. The experimental results show a fluctuation of carbon between positive and negative segregation with distance from slab surface based on the cooling conditions experienced by the slab. Via mathematical analysis, formulae of average macrosegregation level ASL, its fluctuation level FSL and its segregation quality number SQN have been developed. The results calculated by these formulae show good agreement with the description of the formation mechanisms of different continuous casting defects and their locations. Therefore, these calculations illustrated that macrosegregation criteria and their distributions can be considered by experimental, simple and vital tools to evaluate the conditions of surface and inner qualities in continuously cast steel slabs. The mechanisms of these criteria with some mechanisms of continuous casting defects have been explained and discussed.

Continuous casting is the most important route for the production of steel today. Due to the physical, mechanical, and chemical components involved in the production, continuous casting is a very complex process, pushing conventional methods of monitoring and control to their limits. In recent years, this complexity and the increasing global competition created a demand for new methods to monitor and control the continuous casting process. Due to the success and associated rise of machine learning techniques in recent years, machine learning nowadays plays an essential role in monitoring and controlling complex processes. This publication presents a scientific survey of machine learning techniques for the analysis of the continuous casting process. We provide an introduction to both the involved fields: an overview of machine learning, and an overview of the continuous casting process. Therefore, we first analyze the existing work concerning machine learning in continuous casting of steel and then synthesize the common concepts into categories, supporting the identification of common use cases and approaches. This analysis is concluded with the elaboration of challenges, potential solutions, and a future outlook of further research directions.

This chapter contains sections titled: Introduction Model Description Model Validation Parametric study of TC sensitivity to level fluctuations Inverse Heat Conduction Model Conclusions Acknowledgements

In continuous casting (CC) of steel, the water spray cooling system installed in the secondary cooling (SC) zone plays a critical role in controlling its productivity and product quality. In this paper, recent developments in spray cooling applied to the SC are reviewed and evaluated. After introducing the importance of CC in the metal industry and the significance of spray cooling in CC, the development of nozzles and cooling facilities as well as the fundamentals of spray cooling used in the SC zone are presented and discussed. The quantification of heat transfer performance of spray cooling in CC is then studied and the leading correlations developed for the heat transfer coefficient HTC related to major spray cooling parameters are selected and compared. The development of techniques for measuring the essential spray cooling parameters and HTC are also described and assessed. Finally, recommendations on future efforts for developing a better spray cooling system or correlation are provided.

In steel continuous casting (CC), the choice of the appropriate speed at which the slab is cast can be influenced by many different factors and phenomena. While the slab thickness seems to have the biggest impact, other features like the slab width have been consistently overlooked. In fact, the slab width practically limits the casting speed via the mass flow constraint which governs the input and output balance at the tundish. Here, we present a case study that aims at analyzing steel production data from the perspective of casting speed constraints. By studying the speed fluctuations of an industrial CC machine, we identify a strategic regime change toward a stricter consideration of the mass flow constraint. The regime change manifests itself in a significant increase in the correlation between the actual casting speed and the maximal speed associated with the mass flow constraint. On the surface, taking greater account of the input and output balance at the tundish has reduced the productivity of the continuous caster; however, one can argue that the lessened yield is compensated by a diminished risk of eventual slab breaking. From the perspective of this trade-off, we establish a visualization technique that enables us to pinpoint the boundary beyond which one strategic regime becomes economically more advantageous than the other.

In order to predict the dendritic evolution during the continuous steel casting process, a simple mechanism to connect the heat transfer at the macroscopic scale and the dendritic growth at the microscopic scale was proposed in the present work. As the core of the across-scale simulation, a two-dimensional cell automaton (CA) model with a decentered square algorithm was developed and parallelized. Apart from nucleation undercooling and probability, a temperature gradient was introduced to deal with the columnar-to-equiaxed transition (CET) by considering its variation during continuous casting. Based on the thermal history, the dendritic evolution in a 4 mm × 40 mm region near the centerline of a SWRH82B steel billet was predicted. The influences of the secondary cooling intensity, superheat, and casting speed on the dendritic structure of the billet were investigated in detail. The results show that the predicted equiaxed dendritic solidification of Fe-5.3Si alloy and columnar dendritic solidification of Fe-0.45C alloy are consistent with in situ experimental results [Yasuda et al. Int J Cast Metals Res 22:15–21 (2009); Yasuda et al. ISIJ Int 51:402–408 (2011)]. Moreover, the predicted dendritic arm spacing and CET location agree well with the actual results in the billet. The primary dendrite arm spacing of columnar dendrites decreases with increasing secondary cooling intensity, or decreasing superheat and casting speed. Meanwhile, the CET is promoted as the secondary cooling intensity and superheat decrease. However, the CET is not influenced by the casting speed, owing to the adjusting of the flow rate of secondary spray water. Compared with the superheat and casting speed, the secondary cooling intensity can influence the cooling rate and temperature gradient in deeper locations, and accordingly exerts a more significant influence on the equiaxed dendritic structure.

Non-metallic inclusions are present in small volume fractions in steel products. A significant portion of them is associated to the deoxidation process. The type and form of inclusions is, in general, directly connected to the deoxidation practice and to eventual reoxidation during processing. Besides influencing the steel properties, non-metallic inclusions can have an important effect on their processability. In this work, we review the processability questions associated with inclusions in the continuous casting of steel, with emphasis on long products. When solid inclusions are present during the casting of steel they may agglomerate and clog the valves used in the continuous casting equipment, limiting the number of sequential heats that can be casted and reducing casting speeds. Additionally, in some conditions, solid non-metallic inclusions may agglomerate and form surface defects in the continuous casting products, sometimes referred to as scum. As productivity and quality are essential to the profitability of steelmaking, avoiding these conditions is of paramount importance. Thus, we review the main thermodynamic conditions that may lead to the clogging of continuous casting valves, and discuss, from the thermodynamic point of view, the measures that can be taken to avoid the occurrence of these various conditions. Furthermore, we discuss the conditions that might cause to the formation of scum and the thermodynamics of its formation and elimination. It is concluded that the analysis of steelmaking conditions via computational thermodynamics can have an important role in avoiding problems in continuous casting and helping ensure productivity and quality in the process.

This paper analyzes the cooling parameters of the continuous casting speed. In the researches carried out we aimed to establish some correlation equations between the parameters characterizing the continuous casting process, the temperature of the steel at the entrance to the crystallizer, the superheating of the steel and the flow of the cooling water in the crystallizer and different zones of the secondary cooling. Parallel to these parameters were also the values for the casting speed. The research was made for the casting of round ϕ270mm semi-finished steel products. The steel was developed in an electric EBT furnace with a capacity of 100t, treated in L.F. (Ladle - Furnace) and VD (Vacuum-Degassing) and poured in a 5-wire continuous casting plant. The obtained data was processed in MATLAB using three types of correlation equations. The obtained results are presented both in the analytical and graphical form, each correlation being analyzed from the technological point of view, indicating the optimal values for the independent parameters monitored. In the analysis we present a comparison between the results obtained after the three types of equations for each correlation.

Serious defects in the continuous casting of steel, including surface cracks and depressions, are often related to thermal mechanical behavior during solidification in the mold. A finite-element model has been developed to simulate the temperature, shape, and stress of the steel shell, as it moves down the mold in a state of generalized plane strain at the casting speed. The thermal model simulates transient heat transfer in the solidifying steel and between the shell and mold wall. The thermal model is coupled with a stress model that features temperature-, composition-, and phase dependent elastic-visco-plastic constitutive behavior of the steel, accounting for liquid, δ-ferrite, and γ-austenite behavior. Depressions are predicted to form when the shell is subjected to either excessive compression or tension, but the shapes, severity, and appearance differ with conditions. Cracks appearing without depressions are suggested to form in the lower ductility trough when the shell is colder but more brittle. The local thickness of the shell and austenite layer appears to have major effects as well. The model reveals new insights into the formation mechanisms and behavior of surface depressions and longitudinal cracks in the continuous casting process.

A coupled finite-element model, CON2D, has been developed to simulate temperature, stress, and shape development during the continuous casting of steel, both in and below the mold. The model simulates a transverse section of the strand in generalized plane strain as it moves down at the casting speed. It includes the effects of heat conduction, solidification, nonuniform superheat dissipation due to turbulent fluid flow, mutual dependence of the heat transfer and shrinkage on the size of the interfacial gap, the taper of the mold wall, and the thermal distortion of the mold. The stress model features an elastic-viscoplastic creep constitutive equation that accounts for the different responses of the liquid, semisolid, delta-ferrite, and austenite phases. Functions depending on temperature and composition are employed for properties such as thermal linear expansion. A contact algorithm is used to prevent penetration of the shell into the mold wall due to the internal liquid pressure. An efficient two-step algorithm is used to integrate these highly nonlinear equations. The model is validated with an analytical solution for both temperature and stress in a solidifying slab. It is applied to simulate continuous casting of a 120 mm billet and compares favorably with plant measurements of mold wall temperature, total heat removal, and shell thickness, including thinning of the corner. The model is ready to investigate issues in continuous casting such as mold taper optimization, minimum shell thickness to avoid breakouts, and maximum casting speed to avoid hot-tear crack formation due to submold bulging.