Abstract
Eulerian-Lagrangian method is becoming more and more popular for the simulation of dispersed multiphase flow as the computational ability grows. An important issue in this method is the handle of collisions. Until now, both hard-sphere and soft-sphere models have been used extensively in the simulation of gas-solid systems while in gas-liquid systems only the hard-sphere model is used. This study presents an investigation of the performance of the soft-sphere model in gas-liquid systems. The open source software OpenFOAM is utilized to complete our simulations. We simulated the 2D Becker case to give a preliminary study of the suitability of the soft-sphere model in gas-liquid systems. We tested the normal stiffness coefficient from 50 N/m to 0.01 N/m and found that the coefficient 1 N/m predicted sufficiently accurate flow field. In the simulation of 3D Deen case, we tried more stiffness coefficients and found that the soft-sphere model successfully predicted the fluid velocity, and the result at a normal stiffness coefficient of 1 N/m is the optimum. It can be expected that the soft-sphere model is also suitable in gas-liquid systems.
Funding statement: Funding: The authors wish to acknowledge the long term support from the National Natural Science Foundation of China (Grant No. 91434121), Ministry of Science and Technology of China (Grant No. 2013BAC12B01) and State Key Laboratory of Multiphase complex systems (Grant No. MPCS-2015-A-03) and Chinese Academy of Sciences (Grant No. XDA07080301).
References
1. Becker, S., Sokolichin, A., Eigenberger, G., 1994. Gas-liquid flow in bubble columns and loop reactors: part ii. Comparison of detailed experiments and flow simulations. Chemical Engineering Science 49, 5747–5762.10.1016/0009-2509(94)00290-8Search in Google Scholar
2. Busaryev, O., Dey, T.K., Wang, H., Ren, Z., 2012. Animating bubble interactions in a liquid foam. ACM Transactions on Graphics 31, 63–70.10.1145/2185520.2185559Search in Google Scholar
3. Cundall, P.A., Strack, O.D.L., 1979. A discrete numerical model for granular assemblies. Geotechnique 29, 47–65.10.1680/geot.1979.29.1.47Search in Google Scholar
4. Darmana, D., Deen, N.G., Kuipers, J.A.M., 2006. Parallelization of an Euler–Lagrange model using mixed domain decomposition and a mirror domain technique: Application to dispersed gas–liquid two-phase flow. Journal of Computational Physics 220, 216–248.10.1016/j.jcp.2006.05.011Search in Google Scholar
5. Deen, N.G., Solberg, T., Hjertager, B.H., 2001. Large eddy simulation of the Gas-liquid flow in a square cross-sectioned bubble column. Chemical Engineering Science 56, 6341–6349.10.1016/S0009-2509(01)00249-4Search in Google Scholar
6. Delnoij, E., Lammers, F.A., Kuipers, J.A.M., van Swaaij, W.P.M., 1997. Dynamic simulation of dispersed gas-liquid two-phase flow using a discrete bubble model. Chemical Engineering Science 52, 1429–1458.10.1016/S0009-2509(96)00515-5Search in Google Scholar
7. Feng, Y.Q., Schwarz, M.P., Yang, W., Cooksey, M.A., 2015. Two-Phase CFD Model of the Bubble-Driven Flow in the Molten Electrolyte Layer of a Hall–Héroult Aluminum Cell. Metallurgical and Materials Transactions B 46, 1959–1981.10.1007/s11663-015-0355-5Search in Google Scholar
8. Goldschmidt, M.J.V., Kuipers, J.A.M., Van Swaaij, W.P.M., 2001. Hydrodynamic modeling of dense gas-fluidized beds using the kinetic theory of granular flow: effect of coefficient of restitution on bed dynamics. Chemical Engineering Science 56, 571–578.10.1016/S0009-2509(00)00262-1Search in Google Scholar
9. Gruber, M.C., Radl, S., Khinast, J.G., 2013. Coalescence and break-up in bubble columns: Euler-Lagrange simulations using a stochastic approach. Chemie Ingenieur Technik 85, 1118–1130.10.1002/cite.201300024Search in Google Scholar
10. Hoomans, B.P.B., Kuipers, J.A.M., Briels, W.J., Van Swaaij, W.P.M., 1996. Discrete particle simulation of bubble and slug formation in a two-dimensional gas-fluidised bed: a hard-sphere approach. Chemical Engineering Science 51, 99–118.10.1016/0009-2509(95)00271-5Search in Google Scholar
11. Hu, Gusheng., Celik, Ismail., 2008. Eulerian–Lagrangian based large-eddy simulation of a partially aerated flat bubble column. Chemical Engineering Science 63, 253–271.10.1016/j.ces.2007.09.015Search in Google Scholar
12. Lau, Y.M., Bai, W., Deen, N.G., Kuipers, J.A.M., 2014. Numerical study of bubble break-up in bubbly flows using a deterministic Euler–Lagrange framework. Chemical Engineering Science 108, 9–22.10.1016/j.ces.2013.12.034Search in Google Scholar
13. Mattson, M.D., Mahesh, K., 2012. A one-way coupled, Euler–Lagrangian simulation of bubble coalescence in a turbulent pipe flow. International Journal of Multiphase Flow 40, 68–82.10.1016/j.ijmultiphaseflow.2011.11.013Search in Google Scholar
14. Peng, Z., Doroodchi, E., Luo, C., Moghtaderi, B., 2014. Influence of void fraction calculation on fidelity of CFD-DEM simulation of gas-solid bubbling fluidized beds. AIChE Journal 60, 2000–2018.10.1002/aic.14421Search in Google Scholar
15. Sokolichin, A., Eigenberger, G., 1999. Applicability of the standard k–e turbulence model to the dynamic simulation of bubble columns: part i. Detailed numerical simulations. Chemical Engineering Science 54, 2273–2284.10.1016/S0009-2509(98)00420-5Search in Google Scholar
16. Sommerfeld, M., Bourloutski, E., Bröder, D., 2003. Euler/Lagrange calculations of bubbly flows with consideration of bubble coalescence. The Canadian Journal of Chemical Engineering 81, 508–518.10.1002/cjce.5450810324Search in Google Scholar
17. Sungkorn, R., Derksen, J.J., Khinast J.G., 2011. Modeling of turbulent gas–liquid bubbly flows using stochastic Lagrangian model and lattice-Boltzmann scheme. Chemical Engineering Science 66, 2745–2757.10.1016/j.ces.2011.03.032Search in Google Scholar
18. Tomiyama, A., 1998. Struggle with computational bubble dynamics. Third International Conference on Multiphase Flow, ICMF’98, Lyon, France.Search in Google Scholar
19. Xiao, Q., Yang, N., Li, J., 2013. Stability-constrained multi-fluid CFD models for gas–liquid flow in bubble columns. Chemical Engineering Science, 100, 279–292.10.1016/j.ces.2013.02.027Search in Google Scholar
20. Xue, J., Chen, F., Yang, N., Ge, W., 2016. Applicability of the soft-sphere model in bubbly flow, Master Thesis, University of Chinese Academy of Sciences. China.Search in Google Scholar
21. Yang, N., Chen, J., Zhao, H., Ge, W., Li, J., 2007. Explorations on the multi-scale flow structure and stability condition in bubble columns. Chemical Engineering Science 62, 6978–6991.10.1016/j.ces.2007.08.034Search in Google Scholar
22. Yang, N., Wu, Z., Chen, J., Wang, Y., Li, J., 2011. Multi-scale analysis of gas-liquid interaction and CFD simulation of gas-liquid flow in bubble columns. Chemical Engineering Science 66, 3212–3222.10.1016/j.ces.2011.02.029Search in Google Scholar
23. Ye, M., Van der Hoef, M.A., Kuipers, J.A.M., 2004. A numerical study of fluidization behavior of Geldart a particles using a discrete particle model. Powder Technology 139, 129–139.10.1016/j.powtec.2003.10.012Search in Google Scholar
©2017 by De Gruyter
Articles in the same Issue
- Bubble Trajectory in a Bubble Column Reactor using Combined Image Processing and Artificial Neural Network
- Non-linear Radiation Effects in Mixed Convection Stagnation Point Flow along a Vertically Stretching Surface
- Mixing Behaviors of Jets in Cross-Flow for Heat Recovery of Partial Oxidation Process
- Selective Hydrogenation of 4’,4”(5”)-Di-Tert-Butyldibenzo-18-Crown-6 Ether over Rh/γ-Al2O3 Nanocatalyst
- Titania-Loaded Coal Char as Catalyst in Oxidation of Styrene with Aqueous Hydrogen Peroxide
- A Study of the Soft-Sphere Model in Eulerian-Lagrangian Simulation of Gas-Liquid Flow
- Conceptual Approach in Multi-Objective Optimization of Packed Bed Membrane Reactor for Ethylene Epoxidation Using Real-coded Non-Dominating Sorting Genetic Algorithm NSGA-II
- Kinetics of Extraction of Tributyl phosphate (TBP) from Aqueous Feed in Single Stage Air-sparged Mixing Unit
- Viscous Dissipation Effects in Water Driven Carbon Nanotubes along a Stream Wise and Cross Flow Direction
- Evaluation of Mixing and Mixing Rate in a Multiple Spouted Bed by Image Processing Technique
- A Parametric Study of Biodiesel Production Under Ultrasounds
- Numerical Study of MHD Viscoelastic Fluid Flow with Binary Chemical Reaction and Arrhenius Activation Energy
- CFD Analysis and Design Optimization in a Curved Blade Impeller
- Bio-Oil Heavy Fraction as a Feedstock for Hydrogen Generation via Chemical Looping Process: Reactor Design and Hydrodynamic Analysis
- Upgrading of Heavy Oil in Supercritical Water using an Iron based Multicomponent Catalyst
Articles in the same Issue
- Bubble Trajectory in a Bubble Column Reactor using Combined Image Processing and Artificial Neural Network
- Non-linear Radiation Effects in Mixed Convection Stagnation Point Flow along a Vertically Stretching Surface
- Mixing Behaviors of Jets in Cross-Flow for Heat Recovery of Partial Oxidation Process
- Selective Hydrogenation of 4’,4”(5”)-Di-Tert-Butyldibenzo-18-Crown-6 Ether over Rh/γ-Al2O3 Nanocatalyst
- Titania-Loaded Coal Char as Catalyst in Oxidation of Styrene with Aqueous Hydrogen Peroxide
- A Study of the Soft-Sphere Model in Eulerian-Lagrangian Simulation of Gas-Liquid Flow
- Conceptual Approach in Multi-Objective Optimization of Packed Bed Membrane Reactor for Ethylene Epoxidation Using Real-coded Non-Dominating Sorting Genetic Algorithm NSGA-II
- Kinetics of Extraction of Tributyl phosphate (TBP) from Aqueous Feed in Single Stage Air-sparged Mixing Unit
- Viscous Dissipation Effects in Water Driven Carbon Nanotubes along a Stream Wise and Cross Flow Direction
- Evaluation of Mixing and Mixing Rate in a Multiple Spouted Bed by Image Processing Technique
- A Parametric Study of Biodiesel Production Under Ultrasounds
- Numerical Study of MHD Viscoelastic Fluid Flow with Binary Chemical Reaction and Arrhenius Activation Energy
- CFD Analysis and Design Optimization in a Curved Blade Impeller
- Bio-Oil Heavy Fraction as a Feedstock for Hydrogen Generation via Chemical Looping Process: Reactor Design and Hydrodynamic Analysis
- Upgrading of Heavy Oil in Supercritical Water using an Iron based Multicomponent Catalyst