In-situ steel solidification imaging in continuous casting using magnetic induction tomography

: Solidification process in continuous casting is a critical part of steel production. The speed and quality of the solidification process determines the quality of final product. Computational fluid dynamics (CFD) simulations are often used to describe the process and design of its control system, but so far, there is no any tool that provides an on-line measurement of the solidification front of hot steel during the continuous casting process. This paper presents a new tool based on magnetic induction tomography (MIT) for real time monitoring of this process. The new MIT system was installed at the end of the secondary cooling chamber of a casting unit and tested during several days in a real production process. MIT is able to create an internal map of electrical conductivity of hot steel deep inside the billet. The image of electrical conductivity is then converted to temperature profile that allows the measurement of the solid, mushy and liquid layers. In this study, such a conversion is done by synchronizing in one time step the MIT measurement and the thermal map generated with the actual process parameters available at that time. The MIT results were then compared with the results obtained of the CFD and thermal modelling of the industrial process. This is the first in-situ monitoring of the interior structure during a real continuous casting.The SHELL-THICK project has received funding from EU Research Fund for Coal and Steel under grant number 709830. This study reflects only the author's views and the European Commission is not responsible for any use that may be made of the information contained therein

Metal Solidification Imaging Process by Magnetic Induction Tomography

Abstract There are growing number of important applications that require a contactless method for monitoring an object surrounded inside a metallic enclosure. Imaging metal solidification is a great example for which there is no real time monitoring technique at present. This paper introduces a technique - magnetic induction tomography - for the real time in-situ imaging of the metal solidification process. Rigorous experimental verifications are presented. Firstly, a single inductive coil is placed on the top of a melting wood alloy to examine the changes of its inductance during solidification process. Secondly, an array of magnetic induction coils are designed to investigate the feasibility of a tomographic approach, i.e., when one coil is driven by an alternating current as a transmitter and a vector of phase changes are measured from the remaining of the coils as receivers. Phase changes are observed when the wood alloy state changes from liquid to solid. Thirdly, a series of static cold phantoms are created to represent various liquid/solid interfaces to verify the system performance. Finally, a powerful temporal reconstruction method is applied to realise real time in-situ visualisation of the solidification and the measurement of solidified shell thickness, a first report of its kind

Rheological Studies Dedicated to the Development of a Novel Injectable Polymeric Blend for Viscosupplementation Treatment

Viscosupplementation is an intra-articular symptomatic treatment of mild osteoarthritis. The treatment involves the injection of high-molecular-weight hyaluronan (HA), and especially of cross-linked HA to restore the lubricating and cushioning properties of the synovial fluid. This work involves the development of a novel viscosupplementation fluid based on amidated carboxymethylcellulose and obtained by blending the soluble polymer with its crosslinked derivative. Rheological analyses carried out under both oscillatory and continuous shear provided a rationale to assess the viscosupplement formulation and the production process. The hydrogel fraction content and the total polymer concentration can be properly selected in order to ensure an optimal combination of flowability and viscoelastic properties

An Innovative Integrated Method in MHD Design of Electromagnetic Stirrers

Design and optimization of stirrers are complex activities for two main reasons: there is no standard in steelmaking plants, meaning that a personalized design is typically required, and it is not possible to accurately predict the flow induced to liquid steel in the mould. To overcome these complexities two ways can be followed: experimental analysis on scale models and computer-aided numerical simulation. On these basis Ergolines Lab has developed a new design and simulation software tool which is capable to provide engineering solutions and process optimization in times compatible with design requirements, and that can lead to better metallurgical results and lower energy consumption. This paper describes an example of analysis made on a billet caster production facility. In particular, the following has been evaluated: influence of electric operating parameters (current and frequency), influence of process parameters (casting speed and type of entry nozzle adopted)

Heat Flux Estimation in a Continuous Casting Mould by Inverse Heat Transfer Algorithms

Inverse Heat Transfer Problems rely on temperature measurements for the estimation of unknown quantities (e.g. boundary or initial conditions, thermophysical properties); this kind of problems is classified as ill-posed. An application of the inverse analysis in the continuous casting process of steel is here presented. The aim is the estimation of the mould heat transfer starting from temperature measurements, recorded using thermocouples buried inside the copper mould wall. The mould is water-cooled to solidify the hot metal directly in contact with it. The direct stationary conduction problem was solved both on a 2D and a 3D domain. The inverse problem was solved using Gradient algorithms, Genetic Algorithms and SIMPLEX. For both geometries, a good agreement between numerical and experimental temperature values is observed; moreover, the 3D model provides a better estimate of the outlet temperature of the cooling water

Estimation of heat flux distribution in a continuous casting mould by inverse heat transfer algorithms - Paper No. DETC2011-47435

In the continuous casting process of steel, the control of the mould heat removal is a key parameter, since it directly affects the shell growth and the stresses and strains that are produced in the mould. An inverse heat conduction model was developed to calculate mould heat transfer from temperature measurements, recorded using thermocouples buried inside the copper mould wall. The mould is water-cooled to solidify the hot metal directly in contact with it. The direct stationary conduction problem was solved both on a 2D and a 3D domain; the 2D geometry concerns only a longitudinal section of the mould, while in the 3D domain a whole face is considered. The inverse problem was solved using a Conjugate Gradient algorithm, a Genetic Algorithm and the Nelder - Mear SIMPLEX algorithm. For the 3D geometry, the heat flux profile calculated at the axis of the face is close to that obtained from the 2D model, although the former is slightly lower. For both geometries, there is a good agreement between numerical and experimental temperatures. Moreover, the 3D model provides a better estimate of the outlet water temperature

Estimation of Heat Flux Distribution in a Continuous Casting Mould by Inverse Heat Transfer Algorithms

Inverse Heat Transfer Problems rely on temperature measurements for the estimation of unknown quantities (e.g. boundary or initial conditions, thermophysical properties); this kind of problems is classified as ill-posed. An application of the inverse analysis in the continuous casting process of steel is here presented. The aim is the estimation of the mould heat transfer starting from temperature measurements, recorded using thermocouples buried inside the copper mould wall. The mould is water-cooled to solidify the hot metal directly in contact with it. The direct stationary conduction problem was solved both on a 2D and a 3D domain. The inverse problem was solved using Gradient algorithms, Genetic Algorithms and SIMPLEX. For both geometries, a good agreement between numerical and experimental temperature values is observed; moreover, the 3D model provides a better estimate of the outlet temperature of the cooling water