Vanadin är en värdefull metall och kan lakas ur LD (Linz-Donawitz)-slagg med hjälp av vin. Ligander i vinet som lakar vanadin från LD-slagg studerades i denna rapport med mål att identifiera några av deras egenskaper såsom apparent molekylmassa och spektral information. Hyfenerad analys med hjälp av högupplösande vätskekromatografi-mikrovågsplasma med atomemissionspektrometer (HPLC-MP-AES) gjordes för att matcha vanadintoppen från vinet med ett apparent masspann från en gelfiltreringskolonn. Spektral analys visade att det fanns tre misstänkta vanadinligander i det analyserade vinet. Apparent molekylmassa hos liganderna var sannolikt inom spannet 24 Da – 570 Da. / Vanadium is a valuable metal and can be extracted from Linz-Donawitz (LD) converter slag using wine. Ligands in wine responsible for leaching vanadium from LD converter slag were studied in this report in an effort to identify some of their properties such as apparent molecular mass and spectral information. Hyphenated analysis using high performance liquid chromatography-microwave plasma atomic emission spectroscopy (HPLC-MP-AES) was performed to match a vanadium peak from the wine with an apparent mass span from a size exclusion chromatography (SEC) column. Spectral analysis of the vanadium peak revealed that there were three compounds suspected to be ligands to vanadium in the wine analyzed. Apparent molecular mass of the ligands wasfound to likely be between 24 Da - 570 Da.

During the production of steel in the LD converter the refractory lining is exposed to high temperature emulsion of steel, slag and gas. It protects the steel body of the vessel to come in contact with the molten steel.The main purpose of this work was to observe the temperature distribution profile in converter refractory lining which is very important to understand the life of the refractory lining of the LD converter.In this study, a three dimensional (3D) heat transfer model for the refractory lining of converter was developed. The lining of the refractory material was considered as magnesite brick for inner lining, dolomite for intermediate lining and steel shell as outer part. In order to do the numerical modeling, the CFD software Ansys Fluent 13.0 was used. After considering the proper dimensions, meshing, properties of the lining material and boundary conditions, the modeling in Ansys was performed in two stages. In the first stage, the modeling was performed by assuming that the converter is already heated and the inside temperature of the furnace is 1923K and the outside temperature of the steel body is 300K. In the second stage, the temperature change of the molten steel, slag and the gas was considered as function of blowing time and slag height based on theories from different references. Firstly, the three dimensional (3D) heat transfer model was used for the refractory lining of the converter to show transient heat flow through the lining at different times. Secondly, 3D modeling results from fluent 13.0 was used to develop temperature distribution profile through the lining at different height for different time steps and at different positions with time and also along the converter height from the bottom to top. It has been noticed that refractories in the lining in contact with steel and slag must be of good quality for the reduction of wear cost and downtime and therefore the reduction of refractory cost per ton of steel production.

<p>The complexity of industrial systems and the mathematical models to describe them increases. In many cases, point sensors are no longer sufficient to provide controllers and monitoring instruments with the information necessary for operation. The need for other types of information, such as audio and video, has grown. These are examples of information-rich signals for which suitable applications range in a broad spectrum from micro-electromechanical systems and bio-medical engineering to paper making and steel production.</p><p>Recursive parameter estimation algorithms are employed to identify parameters in a mathematical model from measurements of input and output signals. For accurate parameter estimation, the input signal must be <i>persistently exciting, i.e.</i> such that important features of the modelled system are reflected in the output over a sufficient period of time.</p><p>The Stenlund-Gustafsson (SG) algorithm, a Kalman filter based method for recursive parameter estimation in linear regression models, that does not diverge under lack of excitation, is studied. The stationary properties of the algorithm and the corresponding Riccati equation are formulated in terms of the excitation space spanned by the regressor vectors.</p><p>Furthermore, it is shown that the Riccati equation of the studied algorithm can be solved element-wise. Convergence estimates for the elements of the solution to the Riccati equation are provided, directly relating convergence rate to the signal-to-noise ratio in the regression model. An element-wise form of the parameter update equation is also given, where the connection to specific elements of the solution to the Riccati equation is apparent.</p><p>The SG-algorithm is employed for two applications with audio signals. One is in an acoustic echo cancellation setting where its performance is shown to match that of other well-known estimation techniques, such as the normalized least mean squares and the Kalman filter. When the input is not sufficiently exciting, the studied method performs best of all considered schemes.</p><p>The other application is the Linz-Donawitz (LD) steel converter. The converter consists of a vessel with molten metal and foam is produced to facilitate chemical reactions. A common problem, usually referred to as slopping, arises when the foam rises above the limits of the vessel and overflows. A warning system is designed, based on the SG-algorithm and change detection methods, to give alarms before slopping occurs. A black-box model relates different sensor values of which one is the microphone signal picked up in the area above the converter. The system detected slopping correctly in 80% of the blows in field studies at SSAB Oxelösund.</p><p>A practical example of a vision-based system is provided by cavity form estimation in a water model of the steel bath. The water model is captured from the side by a video camera. The images together with a non-linear model are used to estimate important process parameters, related to the heat and mass transport in the LD-converter.</p>

The complexity of industrial systems and the mathematical models to describe them increases. In many cases, point sensors are no longer sufficient to provide controllers and monitoring instruments with the information necessary for operation. The need for other types of information, such as audio and video, has grown. These are examples of information-rich signals for which suitable applications range in a broad spectrum from micro-electromechanical systems and bio-medical engineering to paper making and steel production. Recursive parameter estimation algorithms are employed to identify parameters in a mathematical model from measurements of input and output signals. For accurate parameter estimation, the input signal must be persistently exciting, i.e. such that important features of the modelled system are reflected in the output over a sufficient period of time. The Stenlund-Gustafsson (SG) algorithm, a Kalman filter based method for recursive parameter estimation in linear regression models, that does not diverge under lack of excitation, is studied. The stationary properties of the algorithm and the corresponding Riccati equation are formulated in terms of the excitation space spanned by the regressor vectors. Furthermore, it is shown that the Riccati equation of the studied algorithm can be solved element-wise. Convergence estimates for the elements of the solution to the Riccati equation are provided, directly relating convergence rate to the signal-to-noise ratio in the regression model. An element-wise form of the parameter update equation is also given, where the connection to specific elements of the solution to the Riccati equation is apparent. The SG-algorithm is employed for two applications with audio signals. One is in an acoustic echo cancellation setting where its performance is shown to match that of other well-known estimation techniques, such as the normalized least mean squares and the Kalman filter. When the input is not sufficiently exciting, the studied method performs best of all considered schemes. The other application is the Linz-Donawitz (LD) steel converter. The converter consists of a vessel with molten metal and foam is produced to facilitate chemical reactions. A common problem, usually referred to as slopping, arises when the foam rises above the limits of the vessel and overflows. A warning system is designed, based on the SG-algorithm and change detection methods, to give alarms before slopping occurs. A black-box model relates different sensor values of which one is the microphone signal picked up in the area above the converter. The system detected slopping correctly in 80% of the blows in field studies at SSAB Oxelösund. A practical example of a vision-based system is provided by cavity form estimation in a water model of the steel bath. The water model is captured from the side by a video camera. The images together with a non-linear model are used to estimate important process parameters, related to the heat and mass transport in the LD-converter.

In the steel industry, slag foaming plays a crucial role in many steel processes, given its positive impact on the thermal efficiency of the furnace and its life span. However, excessive foaming causes an overflow in the converter known as “slopping”. Slopping hinders the effectiveness of the processes, especially with the complex and unpredictable foaming rate. This problem occurs mainly in the BOS-processes and after melt tapping to the ladle furnace. The goal of this study is to test and relate a new foaming control system, by blowing a gas (nitrogen or argon) on the surface of the melt to suppress the foam. Firstly, the foaming index of the provided industrial heats for a general LD converter (21 heats) and Outokumpu’s ladle furnace (31 heats) were calculated to find which heat is most likely to slop. Then, a series of experiments were performed to investigate the new foam controlling system’s reliability using a cold model. The results demonstrated that blowing argon instead of nitrogen from the top nozzle suppresses the foam more effectively, which can be attributed to its higher density. Additionally, the optimal argon flow rate required to suppress the foam in worst-case slopping scenarios in the LD converter and the ladle furnace were 874 and 221 m3/min respectively. The provided data further supports the efficacy of this slopping prevention technique, in theoretical and practical aspects. / I stålindustrin spelar slaggskumning en avgörande roll i många stålprocesser, med tanke på dess positiva inverkan på ugnens termiska effektivitet och dess livslängd. Överdriven skumning orsakar emellertid ett överflöde i konvertern som kallas "utkok". Utkok hindrar processernas effektivitet, särskilt med den komplexa och oförutsägbara skumningshastigheten. Detta problem uppstår främst i BOS-processerna och efter tappning till skänkugnen. Målet med denna studie är att testa ett nytt kontrollsystem genom att blåsa en gas (kväve eller argon) på smältytan för att slå sönder skummet. Först beräknades skumindexet för de tillhandahållna industriella chargerna för en allmän LD (21 charger) och Avestas skänk (31 charger) för att hitta vilken charge som har störst risk för utkok. Därefter utfördes en serie experiment för att undersöka det nya skumstyrsystemets tillförlitlighet med hjälp av en kall modell. Resultaten visade att blåsning av argon istället för kväve från det övre munstycket undertrycker skummet mer effektivt, vilket kan hänföras till dess högre densitet. Dessutom var den optimala argonflödeshastigheten som krävdes för att undertrycka skummet i värsta fallet i LD och skänkanläggningen 871 respektive 221 m3/min. De tillhandahållna uppgifterna stöder ytterligare effekten av denna förebyggande teknik, i teoretiska och praktiska aspekter.