ANALYTICAL AND COMPARATIVE INVESTIGATION OF PARTICULATE SIZE EFFECT ON SLURRY FLOW CHARACTERISTICS USING COMPUTATIONAL FLUID DYNAMICS

Abstract

The key issue associated with the industries is the transportation and dumping of solids particulates in the form of slurry at the desired place using long length pipelines. In this perspective, numerical simulation of three-dimensional horizontal slurry pipeline of 0.0549 m diameter using Eulerian two-phase model with RNG k-ɛ turbulence closure is carried out. The glass - beads solid particulates having density ( = 2470 kg/m3) and slurry concentration varies as 10% to 50% (by volume) for velocity ranges of 3-5 ms-1. The computational modeling is done using available commercial software ANSYS Fluent for 125µm and 440 µm particulate size at different velocity and concentration range to know their effect on slurry flow characteristics. It is observed that for chosen particulate size pressure drop increases with increase in velocity at all solid concentration range. The pressure drop in slurry for 440 µm solid particulates is found higher as compared to the pressure drop of 125 µm solid particulates slurry. The percentage change in pressure drop is also reported in the paper due to particulate size effect at all velocity and solid concentration. The obtained results of predicted pressure drop are analytically compared with the available experimental results of literature and are in synchronism with that. A parametric study is carried out with the aim of visualizing and understanding the solid particulate size effect on slurry flow characteristics. Finally, the results of settling solid concentration contour, velocity contour, concentration profiles, velocity profiles and vector representation of concentration/velocity were also predicted for chosen particulates sized slurry.

Keywords

• 3D Slurry Pipeline
• Eulerian Two-Phase Model
• Particulate Size
• Slurry Concentration
• Velocity Distribution
• Pressure Drop

References

1. [1] Colwell JM, Shook CA. The entry length for slurries in horizontal pipeline flow. Can J Chem Eng 1988; 66(5): 714-720. https://doi.org/10.1002/cjce.5450660503.
2. [2] Turian RM, Hsu FL, Selim MS. Friction losses for flow of slurries in pipeline bends, fittings, and valves. Particul Sci Technol 1983; 1(4): 365-392. https://doi.org/10.1080/02726358308906383.
3. [3] Matousek V. Pressure drops and flow patterns in sand-mixture pipes. Exp Therm Fluid Sci 2002; 26(6): 693-702. https://doi.org/10.1016/S0894-1777(02)00176-0.
4. [4] Krampa-Morlu FN, Bergstrom DJ, Bugg JD, Sanders RS, Schaan J. Numerical simulation of dense coarse particle slurry flows in a vertical pipe. In 5th Int Conf Multiphase flow, ICMF 2004; 4: 460.
5. [5] Kraft M. Modelling of Particulate Processes. KONA Powder Part J 2005; 23:18-35. https://doi.org/10.14356/kona.2005007.
6. [6] Kaushal DR, Tomita Y. Experimental investigation for near-wall lift of coarser particles in slurry pipeline Using γ-ray densitometer. Powder Techno, 2007; 172(3): 177-187. https://doi.org/10.1016/j.powtec.2006.11.020.
7. [7] Kumar U, Singh SN, Seshadri V. Prediction of flow characteristics of bimodal slurry in horizontal pipe flow. Particul Sci Technol 2008; 26(4): 361-379. https://doi.org/10.1080/02726350802084564.
8. [8] Lin CX, Ebadian MA. A numerical study of developing slurry flow in the entrance region of a horizontal pipe. Comput Fluids 2008; 37(8): 965-974. https://doi.org/10.1016/j.compfluid.2007.10.008.

9. [9] Chandel S, Singh SN, Seshadri V. Transportation of high concentration coal ash slurries through pipelines. Int Archive Appl Sci Tech 2010; 1: 1-9.
10. [10] Chandel S, Seshadri V, Singh SN. Effect of additive on pressure drop and rheological characteristics of fly ash slurry at high concentration. Particul Sci Technol 2009; 27(3): 271-284. https://doi.org/ 10.1080/02726350902922036.
11. [11] Naik HK, Mishra MK, Rao KU. Influence of chemical reagents on rheological properties of fly ash–water slurry at varying temperature environment. Coal Combus Gasification Products 2011; 3: 83-93.
12. [12] Senapati PK, Mishra BK, Parida BK. Analysis of friction mechanism and homogeneity of suspended load for high concentration fly ash & bottom ash mixture slurry using rheological and pipeline experimental data. Powder Technol 2013; 250: 154-163. https://doi.org/10.1016/j.powtec.2013.10.014.
13. [13] Jiang YY, Zhang P. Numerical investigation of slush nitrogen flow in a horizontal pipe. Chem Eng Sci 2012; 73: 169-180. https://doi.org/10.1016/j.ces.2012.01.027.
14. [14] Kaushal DR, Thinglas T, Tomita Y, Kuchii S, Tsukamoto H. CFD modeling for pipeline flow of fine particles at high concentration. Int J Multiphas Flow 2012; 43: 85-100. https://doi.org/10.1016/j.ijmultiphaseflow.2012.03.005.
15. [15] Kaushal DR, Kumar A, Tomita Y, Kuchii S, Tsukamoto H. Flow of mono-dispersed particles through horizontal bend. Int J Multiphas Flow 2013; 52: 71-91. https://doi.org/10.1016/j.ijmultiphaseflow.2012.12.009
16. [16] Nabil T, El-Sawaf I, El-Nahhas K. Sand-Water Slurry Flow Modelling in a Horizontal Pipeline by Computational fluid Dynamics Technique. Int Water Tech J 2014; 4(1): 13.
17. [17] Silva R, Garcia FAP, Faia Pedro MGM, Rasteiro M.G. Settling suspensions flow modelling: A review. KONA Powder Part J 2015; 32: 41-56. https://doi.org/10.14356/kona.2015009.
18. [18] Gopaliya MK, Kaushal DR. Analysis of effect of grain size on various parameters of slurry flow through pipeline using CFD. Particul Sci Technol 2015; 33(4): 369-384. https://doi.org/10.1080/02726351.2014.971988
19. [19] Pani GK, Rath P, Barik R, Senapati PK. The effect of selective additives on the rheological behavior of power plant ash slurry. Particul Sci Technol 2015; 33(4): 418-422. https://doi.org/10.1080/02726351.2014.990657
20. [20] Assefa KM, Kaushal DR. Experimental study on the rheological behaviour of coal ash slurries. J Hydrol Hydromech 2015; 63(4): 303-310.
21. [21] Swamy M, Díez NG, Twerda A. Numerical modelling of the slurry flow in pipelines and prediction of flow regimes. WIT Trans Eng Sci 2015; 89: 311-322.
22. [22] Wu D, Yang B, Liu Y. Pressure drop in loop pipe flow of fresh cemented coal gangue–fly ash slurry: Experiment and simulation. Adv Powder Technol 2015; 26(3): 920-927. https://doi.org/10.1016/j.apt.2015.03.009.
23. [23] Messa GV, Malavasi S. Improvements in the numerical prediction of fully-suspended slurry flow in horizontal pipes. Powder Technol 2015; 270: 358-367. https://doi.org/10.1016/j.powtec.2014.02.005.
24. [24] Gopaliya MK, Kaushal DR. Modeling of sand-water slurry flow through horizontal pipe using CFD. J Hydrol Hydromech 2016; 64(3): 261-272.
25. [25] Ofei TN, Ismail AY. Eulerian-Eulerian simulation of particle-liquid slurry flow in horizontal pipe. J Pet Eng 2016; 1-10. https://doi.org/10.1155/2016/5743471.
26. [26] Peng W, Cao X. Numerical simulation of solid particle erosion in pipe bends for liquid–solid flow. Powder Technol 2016; 294: 266-279. https://doi.org/10.1016/j.powtec.2016.02.030.
27. [27] Kaushal DR, Kumar A, Tomita Y, Kuchii S, Tsukamoto H. Flow of Bi-modal Slurry through Horizontal Bend. KONA Powder Part J 2017; 34: 258-274. https://doi.org/10.14356/kona.2017016.
28. [28] Assefa, KM, Kaushal DR. A new model for the viscosity of highly concentrated multi-sized particulate Bingham slurries. Particul Sci Technol 2017; 35(1): 77-85. https://doi.org/10.1080/02726351.2015.1131789.
29. [29] Melorie, AK, Kaushal DR. Experimental investigations of the effect of chemical additives on the rheological properties of highly concentrated iron ore slurries. KONA Powder Part J 2017; 2018001. https://doi.org/10.14356/kona.2018001.
30. [30] Naveh R, Tripathi NM, Kalman H. Experimental pressure drop analysis for horizontal dilute phase particle-fluid flows, Powder Technol 2017; 321: 355-368. https://doi.org/10.1016/j.powtec.2017.08.029.
31. [31] Singh JP, Kumar S, Mohapatra SK. Modelling of two-phase solid-liquid flow in horizontal pipe using computational fluid dynamics technique. Int J Hydrogen Energy 2017; 42(31): 20133-20137. d https://doi.org/oi:10.1016/j.ijhydene.2017.06.060.
32. [32] Launder BE, Spalding DB. The numerical computation of turbulent flows. In Numerical Prediction of Flow, Heat Transfer, Turbulence and Combustion, 1983; 96-116. https://doi.org/10.1016/B978-0-08-030937- 8.50016-7.
33. [33] Mohanty S, Parkash O, Arora R. Analytical and comparative investigations on counter flow heat exchanger using computational fluid dynamics. Journal of Computational & Applied Research in Mechanical Engineering 2019; 10.22061/JCARME.2019.4665.1564.
34. [34] Mohanty S, Arora R, Parkash O. Performance prediction and comparative analysis for a designed, developed, and modeled counter flow heat exchanger using computational fluid dynamics. Computational Thermal Sciences: An International Journal 2019; 11(5):423-443. https://doi.org/ 10.1615/ComputThermalScien.2019028520
35. [35] Ahmed SU, Arora R, Parkash O. Flow characteristics of multiphase glass beads-water slurry through horizontal pipeline using Computational Fluid Dynamics." International Journal of Automotive and Mechanical Engineering 2019; 16(2): 6605-6623.
36. [36] Ahmed SU, Arora R, Parkash O. Prediction of Flow Parameters of Glass Beads-Water Slurry flow through horizontal Pipeline using Computational Fluid Dynamics. Jordan Journal of Mechanical & Industrial Engineering 2018; 12(3):197-213.
37. [37] Parkash O, Kumar A, Sikarwar BS. CFD modeling of commercial slurry flow through horizontal pipeline. In Advances in Interdisciplinary Engineering 2019; 153-162. Springer, Singapore. https://doi.org/10.1007/978-981-13-6577-5_16.
38. [38] Ahmed SU, Arora R, Parkash O. Numerical investigations on flow characteristics of sand-water slurry through horizontal pipeline using computational fluid dynamics. J. Therm. Eng 2020; 6(2):128-139.
39. [39] Parkash O, Arora R. Flow characterization of multi-phase particulate slurry in thermal power plants using computational fluid dynamics. J Therm Eng 2020; 6(1):187-203. https://doi.org/10.18186/thermal.672785.
40. [40] Verma OP, Kumar A, Sikarwar BS. Numerical simulation and comparative analysis of pressure drop estimation in horizontal and vertical slurry pipeline. J. Mech. Eng. Sci.. 2020; 14(2):6610-24. https://doi.org/10.15282/jmes.14.2.2020.06.0518.
41. [41] Arora R, Arora R. Thermodynamic optimization of an irreversible regenerated brayton heat engine using modified ecological criteria. J Therm Eng 2020; 6(1): 28-42. https://doi.org/10.18186/thermal.671079.
42. [42] Kaushik SC, Kumar R, Arora R. Thermo-economic optimization and parametric study of an irreversible regenerative Brayton cycle. J Therm Eng 2016; 4(2):861-870. https://doi.org/10.18186/jte.70740.
43. [43] Dalkiliç AS, Cebi A, Celen A. Numerical analyses on the prediction of nusselt numbers for upward and downward flows of water in a smooth pipe: effects of buoyancy and property variations. J Therm Eng 2019; 5(3): 166-180. https://doi.org/10.18186/thermal.540367.
44. [44] Anil S, Dizman T, Celen A, Bilge D, Dalkılıç AS, Wongwises, S. CFD analysis of smoke and temperature control system of an indoor parking lot with jet fans. J Therm Eng 2015; 1(2): 116-130. https://doi.org/10.18186/jte.02276.