# APPLICATION OF COMPUTATION IN METALLURGY

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APPLICATION OF COMPUTATION IN METALLURGY AND MATERIAL SCIENCE TOPIC OF PRESENTATION

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OVERVIEW Metallurgical processes involve complex phenomena of momentum, heat and mass transfer, like in case of sintering process, blast furnace process, welding process etc.. Process simulation of such metallurgical phenomena can give detailed information of fluid flow, heat and mass transfer, and many other relevant informations. Computation provides a great opportunity for modeling and simulating such metallurgical processes. It involves softwares like ANSYS FLUENT, MATLAB, ROSETTA and others, which help in providing an accurate and quantitative description of the process variables.

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COMPUTATIONAL FLUID DYNAMICS

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CFD (Computational Fluid Dynamics) is a branch of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows, heat transfer , stress calculations etc.. CFD makes it possible to numerically solve flow and energy balance in complicated geometries. Commercially available CFD codes use one of the three basic spatial discretization methods FD, FV and FE. FD methods are limited to only “structured grids” whereas FV and FE support both “structured” and “unstructured grids”. INTRODUCTION

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Mesh produced using GEOMESH Mesh produced using T-GRID

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CFD uses “Navier Stokes equations” and “energy balances” over control volumes (the size and number of which is user determined). The solution is then obtained by supplying boundary conditions to the model boundaries and iteration of an initially guessed solution. “ Mesh topology” construction is an important part of CFD modeling, which helps in establishing accuracy of simulation.

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BASIC EQUATIONS IN CFD For cases including Laminar flow, the NAVIER STOKES EQUATION is used, i.e., where, S m = mass added through phase changes or user defined sources. For cases including Turbulent Flow, the κ - ε MODEL is used, i.e., δρ δ t δ ( ρ u) δ x S m = + μ t ρ = C μ κ 2 ε

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CFD SOLVER- FLUENT UNS The FLUENT UNS is a commercially available code written by FLUENT Inc. . It contains the basic elements and equations of CFD, for conducting the CFD simulations. It is a control-volume based technique, which consists of three basic steps, Domain division into discrete control volumes. Integration of governing equations on control volumes to create an algebraic equation for unknowns. Solution of the discretized equations. The governing equations are solved sequentially by performing several iterations, so that convergence can be reached.

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PROBLEM SOLVING STEPS Firstly the model for any specific process is designed. Then, mesh creation is done using either GEOMESH programme or T-GRID programme. After the meshing is completed, then completed geometry is imported to the solver and the following three steps are then performed, The “Boundary Conditions” are set on the model. Then, the “Process Iteration parameters” are set. Finally the “Post-Processing” of the data carried out.

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Velocity vector plot obtained from FLUENT UNS.

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APPLICATION OF CFD

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FIXED BED consists of a fixed layers of small particles arranged in vessel to promote intimate contact between fluids and solids. FIXED BED REACTORS (FBR) have a wide range of applications in chemical as well as metallurgical industries, e.g., in sintering process, in ion-exchange reactions etc. . Main characteristics of these reactors are; Height to Diameter scale. Tube to particle diameter ratio (N). Earlier modeling of FBR was based on large amount of averaging, which was suitable only for large N beds. INTRODUCTION

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CFD modeling of FBR utilizes all the parameters and thus provides a detailed description of the heat transfer & flow processes in both high and low N FBRs. A model of low N FBR known as “44-ball model”, developed using CFD, has been used to study the heat transfer and fluid flow in the fixed bed and to compare the CFD results with the Experimental results.

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This model is the detailed CAD copy of the experimental setup. It is designed to validate the CFD simulations data in more general terms. This specific model is chosen for the following reasons; it provides a predictable and repeatable structure (as it has N=2) which is identical to the experimental setup. its radial heat transfer PECLET NUMBER (Pe r ) is similar to systems with high N value. 44-SPHERE MODEL

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The CAD design of the original 44-sphere model is done in inches. A flat inlet velocity profile is defined at column entrance. The surface mesh is created using a bottom-up technique, where first critical nodes are established from which all edges and faces are created. All the wall-sphere and sphere-sphere contact points are defined. The tube-wall is created with the bottom-up technique, using defined sphere-wall contact point nodes. The “Calming Section” is then modeled, by dividing it into 9 axial sections. MODEL DEVELOPMENT

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Finally, all the above model adaptations are integrated to design the final model. The final model is as shown in the following figure. The front view of the model clearly shows the structure of the N=2 packing.

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Front view of the 44-SPHERE MODEL Top view of the 44-SPHERE MODEL

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MODEL ANALYSIS The 44-sphere model after it is designed, the boundary conditions are set equal to that of the physical experiments. The boundary conditions are, Outlet pressure of model = atmospheric pressure. Wall temperature = 383K Inlet air temperature = 298K Then, following Sphere’s Material specifications are designed : Material Type – NYLON 6,6 . Density = 1300 kg/cm 3 Heat capacity =1000 J/kg. K Heat transfer coefficient = 0.242 W/m. K

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Finally, the under-relaxation factor and residual cutoffs values are set. The other constants that are set , Density of air = 1.225 kg/m 3 . Viscosity = 1.7894 x10 -5 kg/m s Particle diameter = 2.54 x10 -2 m After, completing the above simulation part, “Post Processing” of those data is carried out. It is necessary, to have direct comparison of the CFD data with experimental data. Following Velocity vector plots are obtained by the above post processing. Also, number of such plots representing the data sets are obtained.

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Velocity vector plot for a 2 layer section over the entire bed diameter (legend shows velocity in m/s)

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Velocity vector plot in between two sphere layers (legend shows velocity in m/s)

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Velocity vector plot in between sphere-sphere contact point (legend shows velocity in m/s)

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RESULTS AND CONCLUSION The CFD results obtained are compared with the experimental results and are found to show a good qualitative as well as quantitative fit. The data in results are in the form of radial temperature distribution in the tube, as the radial temperature distribution is of importance to bed operation and is also dependent on internal processes that are modeled. Showing a good quantitative as well as qualitative fit between CFD simulation and experimental results it can be concluded that for the case of low N packed beds CFD simulations are a useful tool for understanding flow and heat transfer principles as well as for modeling these types of geometries.

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Temperature profile plot of CFD data

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Comparison of experimental data and CFD for the 99% near-miss model, at “laminar conditions”, Re = 373, z = 0.420.

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Temperature profile plot of CFD data Temperature profile plot of experiments

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CFD has proved itself as one of the best modeling and simulation tool and provides and also it, provides an in-depth Information about various flow patterns in most of the metallurgical operations. In various other metal processing operations, such as in case of Continuous Caster and Gas stirred melts, the Computational technology has provided the means for better understanding of the inner details of the process There are still many unexplored areas which provide and opportunity for contributions to be made in the field of metal processing operations using computational technology. FUTURE SCOPE

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REFERENCE Verification studies of CFD in Fixed Bed Reactors, BY ir. Michael Nijemeisland. Fluid flow in metals processing : Achievements of CFD and Opportunities, by, J.W.Evans

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