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  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    221

    CFD MODELING FOR PNEUMATIC CONVEYING

    Arvind Kumar1, D.R. Kaushal2, Navneet Kumar3 1Associate Professor YMCAUST, Faridabad 2Associate Professor, IIT, Delhi 3Research Scholar IIT, Delhi e-mail: [email protected]

    Abstract CFD simulation is used to investigate the pressure drop prediction capabilities of CFD techniques for a 900 pipe bend in horizontal plane for an extended range of conveying conditions in a pneumatic pipe line system. The conveyed material was cement with a mean particle size (d50) of 25 micron. In Test Rig, the 900 bend of 52mm internal diameter and D/d of 6 was configured horizontally. The computational grids for the horizontal pipe bend similar to that used in experiment. There is broad qualitative agreement in trends and flow patterns of pneumatic conveying through pipeline system. For the high solids loading ratio the Eulerian solver and transient analysis and at lower solids loading ratios the mixture model and steady-state analysis were more appropriate.

    1. Introduction Pneumatic conveying is widely used in process industries to transport granular materials of different types because of its flexibility of layout compared with other mechanical conveying methods and environmentally friendliness. There are three common modes of transport of material in pneumatically conveying (i) The dilute phase where all the material is normally in suspension flow (ii) Dense phase plug flow for non-cohesive particles with high bulk permeability (iii) Dense phase bed flow for materials with suitable aeration and deaeration characteristics. Several CFD-based models are reported in the literature for the three modes of flow, Mason et al (1998) for dilute phase, Tsuji et al (1992), Xiang and McGlinchey (2004) for dense phase plug flow, Mason and Levy (2001) for dense phase flow.

    A CFD simulation is used to investigate the pressure drop prediction capabilities of CFD techniques across a 900 bend both in a horizontal plane for an extended range of conveying conditions in a pneumatic conveying system.

    Experimental data available in literature used for comparison The experimental data used in the present study for comparison with CFD predictions are of

    McGlinchey et al (2007). The conveyed material was cement with a mean particle size (d50) of approximately 25 micron (d10 = 6.5 micron, d90 = 72.5 micron, approximately). In Test Rig, the 900 bend of 52mm internal diameter and D/d of 6 was configured horizontally with single-ended and differential pressure transducers as shown in Fig. 1 Different conveying conditions were achieved with superficial air velocities at the start of the conveying line

    Fig. 1 Bend geometry and pressure measurement locations (A and B) for pneumatic conveying through horizontal bend.

  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    222

    Mathematical model The use of a specific multiphase model (the discrete phase, mixture, Eulerian model) to characterize momentum transfer depends on the volume fraction of solid particles and on the fulfillment of the requirements which enable the selection of a given model.

    Geometries for CFD simulation The computational grid for the horizontal pipe bend similar to that used in experiments having size of

    5m before bend and 0.8m after bend in horizontal plane and it has 52mm internal diameter. It consists of 300120 hexahedral cells and 322344 nodes has been generated using GAMBIT software.

    Grid Generation The body-fitted coordinate technique was used with the help of the Gambit software package to

    generate three-dimensional grids for bend and straight sections, according to the actual dimensions of the test sections.

    Fig. 2 Meshing at interior of pipe bend (horizontal to horizontal)

    Volume statistics: Minimum volume: 5.5X 10-9 m3 Maximum volume: 9.6X 10-8 m3 Total volume: 4.17 X 10-2 m3

    Face area statistics: Minimum face area: 1.38X 10-6 m2 Maximum face area: 2.47 X 10-4 m2

    Numerical Simulation The grid files generated by Gambit were used for the simulation in Fluent. The experimental conditions

    were approximated using the following assumptions The flow was assumed to be isothermal The flow was assumed to be incompressible The flow was assumed unsteady.

  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    223

    Effects of gravity was accounted for to act in the negative z-direction Multi phase simulations were carried out. The pipe wall roughness was taken smooth A non-slip boundary condition was imposed at the stationary walls, so that velocity at the wall is forced to be zero.

    The different model parameters have been defined as close as possible to the actual experimental conditions and Table 1 shows the selection of model parameters.

    Parameter selection

    Table 1 Selection of different simulation parameters

    Solver Segregated

    Formulation Implicit

    Time Un Steady

    Space 3D

    Velocity formulation Absolute

    Gradient option Cell-based

    Multiphase Eulerian/ Mixture

    Turbulent model Standard k- (2-equation)

    Near-wall treatment Standard wall function

    k- multiphase model Per phase in Eulerian

    In the above simulation specifications, The Eulerian and mixture model is used in Fluent software with standard equations. The discretization method called Phase Coupled SIMPLE was selected for the pressure-velocity coupling while First Order Upwind discretization method was used for other scalar parameters like momentum, volume fraction, turbulent kinetic energy etc. The simulations have been carried out for different test conditions in terms of solid loading ratio, superficial air flow velocity, and volumetric solid concentration and pressure drop values. Inlet boundary conditions such as inlet velocity, volume fraction of solid etc, have been defined according to the experimental parameters. Distribution of cross sectional velocity is reasonable to assume uniform at the bend inlet. At wall, no slip condition is assumed and the wall roughness constant was taken as 0.5. For the convenience of the simulations, spherical mono sized particles were assumed for all solid materials and with this assumption; particle mean diameters were used for the simulations. To define the boundary conditions at the inlet, the velocities of all the phases have to be given. The process of solving a multiphase system is inherently difficult, and usually one may encounter some stability or convergence problems. After each simulation, the velocity and pressure profiles and distribution of solid volume fractions of each phase were inspected. The variations of the above variables with the time were also examined according to the simulation results. Finally, pressure drops across the considered sections for different test conditions were calculated using simulation results and then compared with the experimental observations.

    Grid adaptation for y+ It is essential to make sure that the depth of the wall-adjacent cells fall within the distance over which the log-law is valid (30

  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    224

    Grid independence test The grid independence tests were carried out by refining the initial grid for both type of grid geometry and appropriate number of cells present in the grid. This number was generated by applying the same cross-sectional meshes obtained from the optimum cross-sectional meshes of pipe for the single-phase flow There are 300120 cells consists by horizontal to horizontal bend simulation grid by varying the number of cells for single phase flow and measured pressure drop for judging the optimum mesh sizes.

    Residual convergence The residual sum for each of the conserved variables is computed and stored. In the present simulations, the threshold values were set to a thousandth of the initial residual value of each variable. Fig. 3 shows the residuals for a baseline case for conveying cement.

    Fig. 3 A residual plot for bend simulation for pneumatic conveying through pipe line in horizontal plane, conveying cement at solid loading ratio.

    Boundary conditions At the inlet, velocity and concentrations of the phases were specified as estimated input parameters to match the experimental conditions of the tests. The inlet pressure was not specified and the outlet pressure was specified as an estimate of the experimental conditions. At the wall, the tangential and normal gas velocities were set to zero. The particle diameter and density were taken as a single value of 25 micron and 2500 kg/m3 respectively and there was no mass transfer between the phases.

    CFD modeling results Three-dimensional concentration distributions and pressure drops are modeled using Eulerian two-phase and Mixture models for a 90 degree horizontal pipe bend having bend radius of 156 mm, pipe diameter of 52 mm (bend radius ratio R/r = 6) at different solids loading ratios (SLR; the ratio of solids to air mass flow rates) in the range of about 8 to 119 of cement (with mean particle diameter of 25 micron). The flow velocity was varied from 4.8 to 31 m/s. Modeling results are as given below.

  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    225

    Pressure drop Variation in pressure drop predictions by mixture model for conveying of cement at solid loading ratio is shown in Figs. 4 and 5. As expected, the pressure decreases along the flow constantly, where the effect of pipe bend on flow is absent. However, as the flow reaches near pipe bend, the decrease in pressure is not constant and it decreases rapidly in comparison to the horizontal pipeline. Further, the pressure changes across the pipe bend cross-section with increased pressure at outer wall of the pipe bend.

    The pressure gradient across the bend increases as the solid concentration or flow velocity increases. This increase in pressure gradient may be attributed to the increased interaction between particles at higher concentrations and flow velocities. The bend effect increases on downward side of the pipe as solid concentration increases as the larger pressure gradients take its effect to longer distances.

    Fig. 4 Three-dimensional pressure distribution profile of pneumatic conveying pipe line in horizontal plane, conveying cement at solid loading ratio 119

    Fig. 5 Three-dimensional pressure distribution profile of pneumatic conveying pipe line in horizontal plane, conveying cement at solid loading ratio 18

  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    226

    Concentration distribution Concentration profile for solid loading ratio 119 of cement is shown in Fig. 6 exhibit typical bend effect. It is observed that in upstream side of bend flow behavior is similar to flow in straight pipe section, as the concentration of the flow is maximum towards bottom of the pipe, whereas effect of bend is clearly visible in the downstream of bend. The contour plots clearly show a high particle concentration at the long radius wall of the bend. In the vicinity of outlet, similar high particle concentration could be seen at the bottom area of the conveying pipe. This explains the behaviour of the solid particle inside the bend, specially, at the middle section of the bend where the solid particles are subjected to centrifugal forces and thrown towards the pipe wall. After fading away the centrifugal action, then, the particles are under the gravitational effect and tend to concentrate at the pipe bottom giving high solid volume fraction in the lower half of the pipe cross-section. The concentration distribution profile slightly skewed towards the bottom wall as shown in Fig. 7

    Fig. 6 Three-dimensional concentration distribution profile of pneumatic conveying pipe line in horizontal plane, conveying cement at solid loading ratio 119

    (a) (b) Fig. 7 Three-dimensional concentration distribution profile of pneumatic conveying pipe line in horizontal plane

    at before bend (a) and (b) after bend, conveying cement at solid loading ratio 119

  • Proceedings of the National Conference on Trends and Advances in Mechanical Engineering,

    YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012

    227

    2. Conclusions The ability of the FLUENT software to predict the pressure drop across a 90 degree bend in a pneumatic conveying line transporting cement using standard input parameters is investigated. There is broad qualitative agreement in trends and flow patterns. For the high solids loading ratio (120) the Eulerian solver and transient analysis was reasonably effective with the bend in the horizontal plane. At lower solids loading ratios the mixture model and steady-state analysis were more appropriate.

    References 1. Mason, D.J. and Levy, A. (2001). A model for non-suspension gas-solids flow of fine powders in pipes.

    International Journal of Multiphase Flow, 27(3), 415-435. 2. Levy, A. and Mason, D. J. (1998).The effect of a bend on the particle cross-section concentration and

    segregation in pneumatic conveying systems. Powder Technology, 98 (2), 95-103. 3. Mason, D.J. Levy, A., Mooney, T.and Marjanovic, P. (1997). A comparison of analytical and numerical

    models with experimental data for gas-solid flow through a straight pipe at different inclinations. Powder Technology, 93(3), 253-260.

    4. Tsuji, Y., Tanaka, T. and Ishida, T. (1992). Lagrangian numerical simulation of plug flow of cohesionless particles in a horizontal pipe. Powder Technology, 71(3), 239-250.

    5. Xiang, J. and McGlinchey, D. (2004). Numerical simulation of particle motion in dense phase pneumatic conveying. Granular Matter, 6, 167-172.

    6. Mcglinchey, D., Cowell, A., Knight, E.A., Pugh, J.R., Mason, A. and Foster, B. (2007). Bend pressure drop predictions using the Euler-Euler model in dense phase pneumatic conveying. Particulate Science and Technology, 25, 495-506.