The iron & steel industry are highly material and energy intensive industries. Energy constitutes a significant portion of the cost of steel production, from 20% to 40%. Thus, improvements in energy efficiency result in reduced production costs and thereby improved competitiveness. Another challenge with the steel production is that the CO₂ emissions are high. On an average, primary steel plants emit three tons of CO₂ per ton of steel. The global best is 1.4 tons of CO₂ per ton of steel.
In order to strengthen the green competitiveness and achieve the goal of low-carbon and clean production, Steel industry adopts four strategies of energy savings: (a) Increase the energy efficiency: waste heat recovery, enhancing the efficiency of energy system/equipment optimizing the operation and energy management. (b) Develop and utilize low-carbon fuels such as bio mass, (c) Maximize the value of fuel gas and (d) Develop the end-of-pipe technology such as CCS.
Steel Production Process
In the primary ironmaking process, the raw material like iron ore, coke, and lime are melted in a blast furnace resulting in molten iron (hot metal). The key methods are BOS (Basic Oxygen Furnace) and the more modern EAF (Electric Arc Furnace). In the Secondary steelmaking, the molten steel produced from both BOS and EAF routes is treated to adjust the steel composition. The secondary steelmaking processes involve Stirring, Ladle furnace, Ladle injection, Degassing, CAS-OB (composition adjustment by sealed argon bubbling with oxygen blowing). In Continuous casting the molten steel is cast into a cooled mold causing a thin steel shell to solidify. The shell strand is withdrawn using guided rolls and fully cooled and solidified.
The strand is cut into desired lengths depending on application; slabs for flat products (plate and strip), blooms for sections (beams), billets for long products (wires) or thin strips. In primary forming, the steel that is cast is then formed into various shapes, often by hot-rolling. Hot rolled products are divided into flat products, long products, seamless tubes, and specialty products. Secondary forming techniques give the steel its final shape and properties. These techniques include cold rolling, Machining (drilling), Joining (welding), Coating (galvanizing), Heat treatment (tempering), Surface treatment (carburizing).
Siemens’s Simcenter STAR-CCM+, a Computational Fluid Dynamics (CFD) based offering is used in Steel industry for (a) enhancing the efficiency of energy system and equipment (b) optimizing the operation and energy management (c) Analyzing and comparing various technologies for process optimizations. Simcenter STAR-CCM+ provides detailed analysis of fluid flow, heat transfer and other physio-chemical phenomenon in the equipment at the actual scale, and operating conditions which otherwise is not possible using experimental techniques. This technology gives detailed threedimensional understanding of the process parameters like flow pattern, temperature, mixing profile, chemical composition, heat transfer, combustion, chemical reactions, casting, etc. Simcenter STAR-CCM+ also offers a very robust Discrete Element Method (DEM) capability to model solid particulate flows.
Basic Oxygen Furnace
Basic Oxygen Furnace
The basic oxygen furnace (BOF) is a part of the steel making process where pure oxygen is used to convert molten pig iron into steel by oxidizing carbon. In top-blown furnaces, a supersonic oxygen jet is blown through a vertically oriented lance onto the molten metal bath, creating a cavity at the bath surface. Important parameters are the resulting shape and size of this cavity because they contribute to the interfacial contact area between the oxygen and the metal. The fast decarbonization reactions at the molten metal / gas interface lead to the formation of carbon monoxide (CO), which may react with oxygen in the top space of the furnace to produce carbon dioxide. This latter process is generally referred to as the post-combustion reaction and is highly exothermic (ΔHR = -283 kJ/mol). In order to optimize the energy efficiency of the process and to increase the amount of scrap additions that may be remelted in the bath, there is a strong interest in promoting the post-combustion of carbon monoxide and the transfer of the energy released by this reaction to the liquid metal. Alternatively, bottom-blowing converters are used where the oxygen is injected at the bottom of the furnace. This is leads to additional agitation and mixing, similar to the results shown in the ladle section. Converter geometry, lance configuration, number dimension and positioning of the bottom inlets as well as the flow rates affect the flow field and therefore the oxidation process and this offers opportunities to improve the process and its efficiency.
To simulate a top-lance BOF with a focus on the jet penetration and its interaction with the molten metal Simcenter STAR-CCM+ offers the Volume of Fluid (VOF) method as well as the EulerianmMultiphase model with a model extension to capture the free surface correctly, the so-called LargemScale Interface (LSI). Both methods support reactions in each phase and recently a surface reactionmmodel for VOF was introduced to consider reactions only at the free surface, where oxygen gets in contact with the carbon in the liquid melt.
Case Set-up and description
In the case presented here a pure oxygen jet from above interacts with the melt. The transient VOF simulation is done on a 2D axisymmetric domain with 125.000 hexahedron cells, assuming ideal gas behaviour for the gas phase. Both phases are modelled as multi-component. The gas phase consists of O₂, CO, CO₂ and N₂ while the liquid phase contains Fe and C. To model the decarbonisation, two surface reactions at the interface are applied, forming CO in the gas phase:
C(l) + O₂(g) → 2CO(g)
C(l) + CO₂ → 2CO(g)
2CO(g) + O₂(g) → 2CO₂(g)
Figura 1: Left: Oxygen jet entering the BOF and penetrating the liquid melt. The black line indicates the free surface. Right: Red shows the liquid melt, blue the gas phase, yellowish color indicates liquid droplets.
Results
Simulation results in Fig. 1 show the deep penetration of the oxygen jet into the melt. Smaller and larger melt droplets are lifted up and splash against the wall. The depth and the form of the cavity is permanently changing since this case is inherently transient, resulting on the one hand in a larger surface area and on the other in an additional mixing due to these fluctuations.
Fig. 2 shows the oxygen distribution in the gas phase. At the lance a pure oxygen jet enters the furnace. A part of the oxygen is consumed by the decarbonization at the free surface and another part is converted in the gas phase to carbon dioxide. A closer look to the free surface (Fig. 3 and 4) shows that a lower Carbon content is only found in the vicinity of the free surface. It also indicates that the wiggles are increasing the free surface and therefor the reaction rates significantly, since the lowest C content is found there.
On the gas side, a higher CO mole fraction is found in the wiggles but also on the right-hand side close to the free surface. This is an area where the gas velocities are not that high (see Fig. 3) and CO is not transported efficiently into the bulk.
Ladle Stirring
In a ladle furnace, argon is injected through a refractory-lined lance or through a permeable refractory block in the bottom in order to maintain a uniform temperature and composition. A benchmark exercise for such a furnace is described below. The geometry used and further details are as specified by the German Steel Society’s (VDEh) 7th meeting in 2010.
Problem Description
The ladle holds 185t of steel at 1600oC. Argon is introduced from the bottom giving rise to heterogenous gas plumes causing the steel to be stirred. The goal of the simulation was to determine the time required to achieve complete mixing.
Figure 5: Details for ladle stirring benchmark. Red region: slag and yellow region: the molten metal
A volume-of-fluid (VOF) modelling method was used in STAR-CCM+ to account for the interface between gas and liquid. A discrete particle tracking algorithm to track the injected bubbles (with amRosin Rammler size distribution) and ideal gas law dependent density based on the height of the molten metal was used for the injected gas. Two-way-coupling with consideration of drag, lift and turbulent dispersion force is employed between the gas and the liquid phase. A numerical tracer is introduced to track the extent of mixing and the required mixing time.
Results of ladle benchmark
The results from this study are shown below in Figs. 6(a) to 6(c). Fig. 6a is showing a snapshot of the bubble distribution and rise in the domain. Figure 6b shows the velocity contours of the melt cause by the injection of the Argon jet, clearly showing a developing jet flow with velocity decreasing with height. The velocity magnitude was within 15% of the analytical results. Fig. 6c shows a pictograph from a water-based experiment on a scaled model of the ladle. It indicates that the flow filed matches the simulation results qualitatively (since no velocity measurements were performed in the water experiment). Fig. 7 shows that the mixing time results from simulation (⁓120s) compares well with those from experimental measurements (⁓120-140 seconds) indicating that CFD simulation allows detailed insights in to the flow behaviour. Further geometries can be investigated using simulation combined with an automated direct optimization approach to find an engineering solution to mixing.
Figure 6: (a) Plume of rising bubbles (b) Argon jet velocity field (c) Photo of a scaled water experiment
Figure 7: Comparison of time required for complete mixing with experimental values.
Continuous Casting
After a steel alloy has been manufactured, molten steel needs to be processed for further use. We can discern two kinds of wrought material following the steel production: either ingots that can be used down the line in specific shape casting processes or continuously casted steel rods of various cross section geometries.
Production Challenges
To ensure good overall product quality certain process aspects are key: (a) Transport and location of non-metallic inclusions and slag inside the ingot or strand (b) Temperature management of the alloy to ensure desirable metallurgical properties (c) Defects such as macro and micro shrinkage defects These aspects are closely linked to one another as well as the overall manufacturing efficiency. Thus, the continuous or ingot casting process is a conglomerate of different physical phenomena and engineering challenges involving Heat transfer (radiation, conduction and convection), Phase change (solidification in the metal & boiling due to spray cooling), Material transport, Joule Heating, Magneto Hydro Dynamics (stirring in the strand), Metallurgy including shrinkage defects, Chemical reactions (Exothermic sleeves and powders).
Figure 8: Flow pattern during steel ingot solidification. Creation of alpha pore and shrinkage defects
Problem & Results
Using a pseudo transient approach, Simcenter STAR-CCM+ was used to predict the shell thickness along the strand as well as the position of the solidification tip. The validation work was based on the work of Ushyima where the shell thickness is analytically determined. The caster is assumed to be prefilled with superheated steel, the walls are set to be convective. Inlet speed is also given and at the outlet the casting speed is applied.
Figure 9: Shell thickness validation for single strand caster. Left plot shows the comparison of results. Right plot shows the outline of the geometry after Ushijima
The volume of fluid multi-phase approach is used to investigate the slag-melt- air interaction. Phase change modelling is enabled inside the VOF model. By expanding the computational domain beyond the fluid domain alone to include i.e. the mold or rollers the effect of assumptions in boundary conditions can be mitigated. Simcenter STAR-CCM+ has a set of criteria functions for defect analysis inside the cast part. Material properties are also key to accurately predict flow and solidification behavior inside the cast. The software’s open structure allows one to import own temperature depended material data or you use the materials on offer inside the dedicated metal material database. Results (Fig. 9) indicate that STAR-CCM+ can predict the shell thickness accurately and can be used to evaluate the casting process effectively.z.
Conclusions
Simcenter STAR-CCM+ has been used for the detailed analysis of basic oxygen furnaces, ladle mixing and continuous casting. Details including fluid dynamics, decarbonization reactions on the surface as well as oxidation reactions in the gas phase have been accurately modelled. The Volume of Fluid (VOF) method as well as the Eulerian Multiphase model with a LSI extension can be used to capture the free surface correctly. Siemens Simcenter STAR-CCM+ opens the door to further optimization and process improvement.
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