OPTIMIZATION OF THE CLEAN STEELS LADLE TREATMENT AND NON-METALLIC INCLUSION CONTROL. K.V. Grigorovich, S.S. Shibaev

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1 OPTIMIZATION OF THE CLEAN STEELS LADLE TREATMENT AND NON-METALLIC INCLUSION CONTROL K.V. Grigorovich, S.S. Shibaev Baikov Institute of Metallurgy and Material Science, RAS, Leninskii Pr., 49, Moscow Russia, , 1. Introduction The content, origin, size and distribution of oxide inclusions significantly influence the quality of tire cord, railway wheel, bearing and stainless steel grades. The control of nonmetallic inclusions allows us to predict the steel properties however modern methods of nonmetallic inclusions evaluation are highly labor and time-consuming. Fractional Gas Analysis (FGA) method developed is a modified oxygen determination method realized under nonisothermal conditions. Fractional gas analysis (FGA) is based on the difference in temperature of the thermodynamic stability of oxides. It provides a possibility to separate and identify the oxides in steel. The first attempts to elaborate a gas fusion technique for the separation of oxides from the steel samples upon monotonous or step-wise heating with IR detector have been realized in 80 th [1]. The progress of earlier works was not, however, succeeded by the extensive practical use of the temperature ramping technique. This fact was mainly related to two problems. One of them was the absence of numerical algorithm and software for data processing of complicated non isothermal kinetic data. The second problem consisted in identification of oxides and was related to the start temperatures of carbothermal reduction of oxides Ts in analytical melt. The above problems have been worked on for recent years. First, to process the results of temperature ramped analysis [2] an OxSeP original software has been developed and implemented on the modern TC-600 LECO gas analyser. The numerical procedure involved consecutive separation and subtraction of individual peaks from the total evolution curve. The temperature-dependent background evolutions as well as mixing effects in a gas system of analyzer were also treated by this model. Second, a thermodynamic model of carbon reduction of oxides present in the form of inclusions in a molten sample, saturated with graphite during FGA has improved [3-4]. And finally, identification OxID software, which includes a thermodynamic model of carbon reduction of oxide inclusions during the analysis, has been improved [5]. The aim of this work was to apply the improved FGA procedure of oxide speciation for inclusion control in clean steels, using the temperature ramping technique realized on commercially available instruments such as TC-600 LECO analyzer. Experimental The rail-wheel, railway, and tire cord steels sampled in the course of ladle treatment processes and were investigated by FGA method. The content of non-deformable inclusions in these steel samples has been studied using a TC-600 LECO analyzer and the original OxSeP software. The FGA results were compared with data on inclusions control obtained by Image analysis on IA-32 LECO Analyzer and X-ray microprobe analysis results. The results obtained showed the high reproducibility of oxide identification procedure. It was shown that the FGA application allowed us to find a number of harmful oxide inclusions - aluminum silicates and spinels, identified as non-deformable, to predict their influence on the steel quality and to detect sources of their origin during the ladle treatment process. The procedures of steel cleanliness control for tire cord and railway steels by the Image analysis and FGA were developed. 1

2 Figure 1 shows typical FGA result of data processing for a railway steel sample. The curve of CO evolution from specimen is a sum of peaks. Each peak is a result of reduction of a particular kind of oxide inclusion. The OxID calculated identification parameters are the temperature of the oxide reduction beginning -Ts, temperature of peak maximum -Tmax to define certain kind of supposed oxide inclusions in the steel grade. As a final result of the real experimental data treatment by "OxSeP", one can obtain the total oxygen and surface oxygen contents, oxygen content in oxides as a sum of oxygen corresponding to peaks and a set of oxygen content for each peak having its own model temperatures. Fig. 1 FGA data for a railway steel sample. The calculated model parameters: Ts is the start temperature of the oxide reduction and Т max is the temperature of peak maximum. Wheel steels Non-metallic inclusion nucleation and steel refining are characterized through various oxidation and reduction processes coinciding with changes in liquid steel s oxygen activity. Steel purity, quality and production cost widely depend on reliable oxygen control. Figure 2 presents calculated equilibrium oxygen solubility in wheel steel as a function of deoxidizers concentrations at K with allowance for deferent reactions products such as MnO, SiO 2, Al 2 O 3 or 2CaOSiO 2. The marks are the results of industrial experiments in 130t ladle at the Viksa Metalurgical Plant. Where Ot is the total oxygen measured in probe by using TC-600 LECO analyzer and Os is the real dissolved oxygen recalculated from the oxygen activity data measured by Celox Hereaus-Electro-Nite oxygen sensors. Aluminum, silica-calcium powder in steel wire and carbon (for vacuum deoxidizing process) were used in experiments to control oxygen in steel. The experimental results agree adequately with the calculated oxygen solubility. The calculations shows that the silica-calcium application for 2

3 deoxidizing of wheel steel melt leads to the oxygen content of more than 20 ppm at the 1873K and silicon concentration of less than 0,3%. The results of the experiments show that, after infeeding of Si-Ca in steel wire and argon blowing the oxygen content in steel more than 25 ppm. The oxygen content of less than 20 ppm can be obtained in liquid steel without recourse of the strong deoxidizers using vacuum degassing of melts with a carbon concentration of more than 0,5 mass%. Fig. 2 Calculated oxygen solubility in wheel steel melt at 1873K as a function of deoxidizers concentrations with different reactions products: CO, MnO, SiO 2, Al2O 3 and 2CaOSiO 2. Ot - total oxygen content; Os oxygen dissolved. Figure 3 presents the FGA results the mean values and Standard deviation for steel probes that were sampled from the ladle furnace(lf) and the ladle vacuum degasser(ld) during the ladle and vacuum treatment of wheel steels. All the peaks were divided into three groups according to the chemical composition of oxides identified using by the original OXID software. The first group of peaks with Tmax < K was attributed to silica and manganese silicates. The second group of peaks was attributed to alumina and complex spinels more harmfull hard deformable inclusions. The third group of peaks was attributed to complex (Mg,, Ca, -reach ) - silicates. Figure 3 allow us to estimate the influence of ferroalloys and deoxidizers additions during laddle treatment on the total oxygen and nitrogen contente as well as the amount and content of different oxide inclusions in steel melt. The oxygen content in the form of calcium aluminates and magnesium spinels increases (Probe 4) from 21,3 to 27,9 ppm just after the SiCa wire infeeding in the steel melt. The oxygen content in the form of aluminates decreases simultaneously from 20,3 to 8,8 ppm as a result of inclusion modification and assimilation with the slag. The total oxygen content and oxygen content in the oxide form abruptly decreased from 42,8 to 12,7 ppm (Probe 5) as a consequence of vacuum degasing. 3

4 Fig. 3 Quantitative changes of total oxygen and nitrogen content and oxygen content in different oxide groups according FGA results during the ladle and vacuum treatment of wheel steels the mean values and Standard deviation. Rail steels Nonmetallic inclusions which are present in a matrix in a significant amount, are known to be main sites of fatigue crack nucleation. Therefore, to improve the quality of rail steel, it is of importance to develop methods allowing the control of quantitative and qualitative compositions of nonmetallic inclusions. It is of importance to choose a proper method of controlling the content of nonmetallic inclusions in steel and the assessment criteria for results of measurements. Thus, the problem of the method that can provide complete information on the steel cleanness of rail steels remain unsolved. The volume fraction of inclusions clearly illustrates the contamination of a metal. The content of coarse nondeformable inclusions in a metal is known to control the damage of rails induced by contact-fatigue defects. If we assume that the source of primary fatigue cracks in a metal is represented by nondeformable inclusions whose size is higher than a critical size, the volume fraction of coarse inclusions in a metal should determine its tendency to form contact-fatigue-crack nuclei. We studied the samples of rails of experimental batches produced at the OAO Novokuznetsk Metallurgical Works (NKMK), OAO Nizhni Tagil Metallurgical Works (OAO NTMK), Nippon Steel Corporation, Nippon Kokan Keisha, Sogerail, Voest-Alpine, and Guta Katowice. The results of operation of the rails and the results of their full-scale wear tests performed at the Russian experimental ring in Scherbinka indicate that the rails have substantially different characteristics. Using the FGA data, we can rapidly determine the volume fraction of oxide inclusions in the steels. This parameter characterizing the metallurgical purity of steel, is estimated by quantitative metallography, and is controlled by a number of documents. These are Russian GOST , method P; DIN 50602, method K; and ASTM-E45, method D. The volume fraction of inclusions is calculated according to the Cavalieri Akkern principle as the ratio of the area occupied by an inclusion to the analyzed polished-section area. Since FGA can 4

5 quantitatively determine the oxygen content in each type, we can easily show that it can calculate the volume fractions of oxide inclusions with a higher accuracy as compared to that of metallographic methods. For this purpose, we use the formula: V NI = SNI ρsteel = S sec 100 n i= 1 O ρ ОX ОX М ym ОX O where Ssec is the analyzed area of the polished section, SNI is the total area of the detected sections of nonmetallic inclusions, ρ steel and ρ OX are the density of steel and oxides of a given composition, respectively accordinelly, M O is the atomic mass of oxygen, Mox is the oxide molecular mass, y is the stoichiometric coefficient outside oxygen atom in the oxide formula, and Oox is the FGA determined content of oxigen (wt %) bound in the oxide of the inclusions type. Fig 4 Comparison of volume fractions of oxides inclusion in a rail steel determind by FGA and quantitative metallograpy In Fig. 4, we compare the volume fractions of oxide inclusions in a rail steel obtained by FGA and quantitative metallography. The approximating line y = ax corresponds to an approximation coefficient of 0.91, which indicates satisfactory agreement between these results. The volume fractions of inclusions determined by FGA are seen to be slightly higher than the values obtained by quantitative metallography, which is related to the fact that the metallographic sensitivity is restricted to the resolution of the optical microscope. Moreover, the probability of detection of coarse inclusions on a polished section is low; however, coarse inclusions substantially contribute to the total oxygen content. Using the FGA results, we plotted the oxygen content in oxide inclusions of various types in rail steels versus their service durability (Fig. 5). We calculated the oxidic cleanness of steel (OCS) with allowance for the contributions of inclusions of various types to the formation of contact-fatigue cracks. The OCS is shown to predict the service durability of rails with a correlation coefficient R2 =

6 Fig 5 Oxidic cleanness of steel (OCS), which specifies the amount of oxide inclusions of various types in a rail steel, as a function of the service durability of the rails mounted in the experimental ring. Tire cord steels Tire cord steel quality is especially sensitive to cleanness in non-metallic inclusions. Hardly deformed non-metallic Al 2 O 3 inclusions in high strength tire cord steel are one of the principal causes of the fall in productivity (wire failure during drawing and spin breakage). Low-melting and easily deformed inclusions from the point of view of their influence on the steel characteristics are the least harmful. Precipitation of hardly deformed quartz or corundum will take place if Al 2 O 3 inclusions content is less 10% or more 35%, respectively. The set of tire cord rod samples of different producers were tested by using the fractional gas analysis method realized on TC-600 LECO gas analyzer with original OxSeP software use. FGA is sensitive to the composition of inclusions only and rather than to their size. These rod samples were produced using different raw materials and technologies. The chemical composition of these steel grades samples was very close, mass. %: С 0,70-0,81, Mn - 0,41-0,54, Si 0,15-0,24. Fig 5 represents correlations of temperatures of the main peak maximum T M on the FGA curves, concentrations of the aluminum dissolved in steel and portions of alumna inclusions (relative %). Such an adequate correlation demonstrates the FGA possibilities for tire cord steel cleannes control. The dashed line is the OxId prediction of the temperature of the maximum (Т M ) of the main peak for alumna (----) and silica (- - -) inclusions. For the concentration interval lower 20 ppm for aluminum dissolved in steel the predicted temperatures Т M of peak show that the main peak can be identified as silica inclusions. The main peak in the FGA curve for the samples with aluminum dissolved in steel of higher than ~40-50 ppm can be related to alumna inclusions. 6

7 Fig 5 Tire cord samples investigation. Correlations of T M of the main peaks, with the concentrations of aluminum dissolved in steel and portions of alumna inclusions, relative %. Figure 6 is displays the cooperative results of the FGA namely, mean values and Standard deviation for tire cord rod samples of 4 Heats Saar Stahl Plant production (A, B, C, D), of Nippon steel NS, Byelorussian metallurgical plant BMZ and Moldavian metallurgical plant (MMZ) production. The peaks were divided into the three groups according to the chemical composition of oxides and bulk analysis results for the metal and original OXID software calculations. The first group - peaks with Tmax < K are attributed to silica and manganese silicates. The second group - peaks are attributed to alumina and complex spinel (Mg, Al) - hard deformable harmful inclusions. The third group of peaks are attributed to complex (Ca, Al-reach ) - silicates. The higher the temperature of peak the higher the content of (Ca, Al) in silicates. It was found that oxide peaks spectrum was similar for all tested A, B, C, D of Heats samples. It should be particularly mentioned that the FGA evolution curve has a main peak with highest oxygen content. The oxide spectra in heats A,B,C,D, are generally very similar. This can be deduced from the fact that the shape of the evolution curves and the temperature of the maximum gas evolution are very close. The temperatures of the maximum in the gas evolution curves are very close to those predicted for silica inclusions ( K). This means that the amount of alumina inclusions is very low and most of inclusions are deformable silicates. 7

8 silicates hard deformable silicates Al, Ca, Mg rich silicates total oxygen in oxides Oxygen content, ppm A B C D BMZ NS MMZ Heat Fig. 6. Results of fractional gas analysis of cord steel (mean and standard deviation). Conclusions The use of OxSeP and OxId software for a wide class of the steel grades is characterized by a high accuracy of the oxide separation and identification results. OxSeP and OxId software can be successfully used in different fields of metallurgy and material control. The results obtained showed the high reproducibility of oxide identification procedure It was shown that the FGA application allowed us to find a number of harmful oxide inclusions, to predict their influence on the steel quality and to detect sources of their origin during the ladle treatment process. The procedures of steel cleanliness control for tire cord and railway steels by the Image analysis and FGA were developed. The FGA was shown can be successfully used for the steel quality control and prediction of the steel properties. References [1]. R. Prumbaum, K. Orths: Gießerei Forsch, 31(1979), (2/3), 71. [2]. K.V. Grigorovitch, A.M. Katsnelson, A.S. Krylov, AV. Vvedenskii: Proceedings Analytical Chemistry in the Steel and Metal Industries, 4th Intern. Conf. Proc., Luxembourg, 1995, p.527. [3]. P.V. Krasovskii, K.V. Grigorovitch: Metally, 2002 (2002), 2, 108. [4]. P.V. Krasovskii, K.V. Grigorovitch: Metally, 2001 (2001), 4, 337. [5]. K.V. Grigorovitch, P.V. Krasovskii, S.A. Isakov, A.A. Gorokhov, A.S. Krylov: Industrial Lab., 68 (2002), 9, 3. 8