Experimental and mathematical modeling studies on primary hot metal desulfurization

Transcription

1 Experimental and mathematical modeling studies on primary hot metal desulfurization February 20, 2018 Tero Vuolio Research Unit of Process Metallurgy University of Oulu

2 Tero Vuolio Doctoral Student in the Process Metallurgy Research Unit (10/2017 ) Educational background: M.Sc. (Tech.) in Process Engineering Year of enrolment 2013 Graduated in 2017 Previous working history in metallurgical industry: SSAB Europe Oy at Raahe (5/2016 9/2017) Outokumpu Oy at Tornio (5/2014 8/2014 & 5/2015 8/2015) Tero Vuolio

3 A brief introduction to HMD Tero Vuolio

4 Hot metal desulfurization The purpose of hot metal desulfurization is to extract sulfur from hot metal to the top-slag Due to the fact the desulfurization demands reductive conditions, the hot metal desulfurization is most efficient to be carried out prior to converter process Fig. 1 Phenomena in a hot metal ladle during the hot metal desulfurization via powder injection (Visuri et al. 2018). Powder injection tehnique A more or less standardized method to conduct hot metal desulfurization is a so-called powder injection tehnique In powder injection, a typically fine-grade reagent is injected into hot metal via immersed lance Suitable desulfurization reagents include lime*, calcium carbide, magnesium, soda ash*, limestone* (*This study handles) Tero Vuolio

5 The powder injection based hot metal desulfurization constitutes of two main reactions, which are: i) Transitory contact reaction (Reagent-metal) ii) Permanent contact reaction (Top slag-metal) Fig. 2 Diffusion of calcium and sulfur ions in CaS-layer (Oeters 1994) Tero Vuolio

6 Main research topics Experimental studies on kinetics of resulfurization (Sulfur pickup) - The objective of work is to study the kinetics of resulfurization - The resulfurization occurs via permanent phase contact. Sulfur is transferred from slag to metal phase. - A fundamental question to be answered is that does a resulfurization of hot metal occur during the transferring of hot metal ladles? - Is the phenomenon relevant in the view point of steel manufacture? Mathematical modeling studies on primary hot metal desulfurization - The scope of the work is to create a prediction model with an adequate prediction performance - The effect of particle size distribution on the kinetics of hot metal desulfurization is of great importance - The modeling is conducted is based on the combination of mass-transfer theory and datadriven modelling techniques Tero Vuolio

7 Resulfurization (= Sulfur pick-up)

8 Aspects on Resulfurization The resulfurization of hot metal can occur in various stages through permanent phase contact (= Sulfur is transferred from slag to metal phase) The resulfurization is assumedly controlled by mass-transfer in the slag-metal interface (1 st order kinetics) The sulfur capacity of top-slag determines the sulfur distribution between slag and metal Fig. 3 Possible occurrence of resulfurization during the processing of hot metal. Thus, the magnitude of the thermodynamic driving force is determined by the properties of slag In high temperatures, the basicity of the top-slag (B 2 ) can be considered to significantly increase the sulfur distribution However, as the primary desulfurization operates in relatively low temperatures, the top-slag constitutes mainly of unsoluted lime particles (Not Ca 2+ ), and thus the high basicity is not realized as an increased sulfide capacity Tero Vuolio

9 Experimental setting - The main independent variable is the Na 2 O-content of top-slag - Argon atmosphere - Constant temperature - Constant sulfur content in both phases To evaluate the generalizability to a full-scale process, the dimensional homogeneity is determined for experiments: - Hot metal = g - Slag = 6.78 g - [S] = p-% - (S) = 3.5 p-% - T = 1350 C Slag CaO (%) Na2O (%) SiO2 (%) CaS (%) CaO/SiO2 (Na2O+CaO)/SiO2 Na2O/SiO2 Exp. 1 77,00 0,00 15,10 7,87 5,10 5,10 0,00 Exp. 2 74,32 3,20 14,57 7,87 5,10 5,32 0,22 Exp. 3 71,72 6,30 14,06 7,87 5,10 5,55 0,45 Exp. 4 68,60 10,10 13,45 7,87 5,10 5,85 0, Tero Vuolio

10 Preparation of the slag phase The slag phase was prepared in a chamber furnace by applying a following heating sequence: - Temperature rate of change 600 C/h - Maximum temperature 1400 C/h - Holding time 2 h Initial compounds: - CaO (> 99.9 %) - CaS (> 97 %) - Na 2 CO 3 (> 99.9 %) - SiO 2 (> 99.7 %) Fig. 4 Slag phase after thermal pre-treatment Tero Vuolio

11 Experimental setting Argon atmosphere Constant temperature Test sequence is as follows: 1. Hot metal phase is melted 2. Temperature of the system is decreased to 1350 C 3. Initial sample at t = 0 4. Slag phase is set on the hot metal phase 5. The sampling of hot metal is conducted in every 5 minutes during the time period of 0-20 min, and in every ten minutes during the rest of the experiment 6. Overall duration of the experiment is 120 min 11 Fig. 5 A schematic illustration of the applied apparatus Tero Vuolio

12 - The rate constant for resulfurization is solved by means of least-squares (Crucible) - OBS! The following curves have been determined for average rate constant! - The resulfurization curve for a full-scale process is determined by applying the dimensional homogeneity - The modeling results have to be validated in industrial scale Repetition Test-series k (1/s) Sum of squares Ls (t90) Na2O 1 2 0,0050 0,8 151,5 3, ,0050 0,03 137,7 3, ,0040 0,02 192,6 3,2 avg 2 0,0046 0,02 160,6 3,2 Repetition Test-series k (1/s) Sum of squares Ls (t90) Na2O 1 4 0,0027 0,05 235,4 10, ,0018 0,06 253,1 10, avg 4 0,0022 0,05 244,3 10,1 Ladle Crucible 12 Fig. 6 Evolution of sulfur content of the metal phase

13 A prediction model for hot metal desulfurization

14 d S dt = k tot( S S eq ), [1] A short description: A scope of the work is to create a prediction model with an adequate prediction performance for end sulfur content in hot metal k i,dp = β S 6 d p mሶ r ρ Fe t m Fe ρ res, [2] r The effect of particle size distribution on the kinetics of the transitory reaction is of great importance The model has to be suitable for on-line use k tot = e b b 0k j tot, [3] A main problematique is related to complexity of certain phenomena occuring in the hot metal ladle The uncertainties in the system identification are mainly related to interfacial area between the emulsified reagent particles and the hot metal phase k tot = e b 0 6 d p b 1 b 2 Qtot ሶ m r ρ r b 3 ρfe m Fe b 4 ε. [4] The end sulfur content is solved analytically by applying a so-called surface area approximation Surface area approximation is based on the solid surface area that is available for extraction of sulfur via the injected reagent particles M min i=0 S t,i [ [S] 0,i S eq e ( (eb 0 b 6 1Qtot,i b 2 d p,i ሶ m r,i ρ r b 3 ρ Fe m Fe,i b 4)t)+ S eq ] 2. [5] The unknown factors are identified (= quantified ) by solving the parameter vector by means of least-squares Eq. 5 Two numerical solution strategies combined with a cross-validation procedure are applied: 1. Genetic algorithm 2. Nelder-Mead algorithm Tero Vuolio

15 Table III. Comparison between prediction approaches for end sulfur content for the whole data (Vuolio et al. 2018). Model R 2 MAE t res Surface area approach (RRS) Surface area approach (Sauter) Surface area approach (RRS, Limited contact, Q tot ) Linear reagent efficiency model Parameterized rate constant Fig. 7 Fit (Vuolio et al. 2018). Table II. Identified modelling coefficients (Vuolio et al. 2018). Method Cost-function b 0 b 1 b 2 b 3 b 4 R 2 MAE SOS MLR Best solution Linear GA Best solution Non-linear Nelder-Mead Best solution Non-linear Table IV. Results of the external validation (Vuolio et al. 2018). Method Cost-function R 2 SOS MAE [wt-%] MLR Best solution Linear GA Best solution Non-linear Fig. 8 Validation (Vuolio et al. 2018). Nelder-Mead Best solution Non-linear Tero Vuolio

16 Conclusions Kinetics of resulfurization: 1. The resulfurization of hot metal is an existing phenomenon. According to dimensional homogeneity it can be established that resulfurization is a relevant phenomenon, and its occurrence during the manufacture of hot metal has to be evaluated. 2. With a careful slag modification with an alkaline flux it is possible to increase the sulfide capacity of the slag phase, and thus to reduce the rate of resulfurization through the control thermodynamic driving force. Prediction model for hot metal desulfurization: 1. Without an adequate measure of the particle size distribution of the applied desulfurization reagent, the prediction of the end sulfur content is not accurate, regardless of the applied type of the prediction model. A parameterized expression of the surface area approximation can be applied in prediction, if the residence time and mass transfer coefficient are substituted with a pre-exponential bias-term. 2. It is rather obvious that the effective surface area of the injected reagent particles is significantly smaller than the nominal surface area of the particles Tero Vuolio

17 Thank you! Questions?