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The effect of turbulence on mass transfer rates of small inertial particles with surface reactions

Published online by Cambridge University Press:  13 December 2017

Nils Erland L. Haugen*
Affiliation:
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Kolbjørn Hejes vei 1B, NO-7491 Trondheim, Norway SINTEF Energy Research, N-7465 Trondheim, Norway
Jonas Krüger
Affiliation:
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Kolbjørn Hejes vei 1B, NO-7491 Trondheim, Norway
Dhrubaditya Mitra
Affiliation:
Nordita, KTH Royal Institute of Technology and Stockholm University, Roslagstullsbacken 23, SE-10691 Stockholm, Sweden
Terese Løvås
Affiliation:
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Kolbjørn Hejes vei 1B, NO-7491 Trondheim, Norway
*
Email address for correspondence: [email protected]

Abstract

The effect of turbulence on the mass transfer between a fluid and embedded small heavy inertial particles that experience surface reactions is studied. For simplicity, the surface reaction, which takes place when a gas phase reactant is converted to a gas phase product at the external surface of the particles, is unimolar and isothermal. Two effects are identified. The first effect is due to the relative velocity between the fluid and the particles, and a model for the relative velocity is presented. The second effect is due to the clustering of particles, where the mass transfer rate is inhibited due to the rapid depletion of the consumed species inside the dense particle clusters. This last effect is relevant for large Damköhler numbers, where the Damköhler number is defined as the ratio of the turbulent and chemical time scales, and it may totally control the mass transfer rate for Damköhler numbers larger than unity. A model that describes how this effect should be incorporated into existing simulation tools that utilize the Reynolds averaged Navier–Stokes approach is presented.

Type
JFM Papers
Copyright
© 2017 Cambridge University Press 

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References

Bec, J., Biferale, L., Cencini, M., Lanotte, A., Musacchio, S. & Toschi, F. 2007 Heavy particle concentration in turbulence at dissipative and inertial scales. Phys. Rev. Lett. 98, 084502.CrossRefGoogle ScholarPubMed
Brosh, T. & Chakraborty, N. 2014 Direct numerical simulation of a pulverized coal jet flame employing a global volatile matter reaction scheme based on detailed reaction mechanism. Energy Fuels 28, 60776088.CrossRefGoogle Scholar
Brosh, T., Patel, D., Wacks, D. & Chakraborty, N. 2015 Numerical investigation of localised forced ignition of pulverised coal particle-laden mixtures: a direct numerical simulation (DNS) analysis. Fuel 145, 5062.CrossRefGoogle Scholar
Chen, C., Horio, M. & Kojima, T. 2000 Numerical simulation of entrained flow coal gasifiers. Part II. Effects of operating conditions on gasifier performance. Chem. Engng Sci. 55, 38753883.CrossRefGoogle Scholar
Chen, L, Yong, S. Z. & Ghoniem, A. F. 2012 Oxy-fuel combustion of pulverized coal: characterization, fundamentals, stabilization and CFD modeling. Prog. Energy Combust. Sci. 38, 156214.CrossRefGoogle Scholar
Deen, N. G. & Kuipers, J. A. M. 2014 Direct numerical simulation of fluid flow accompanied by coupled mass and heat transfer in dense fluid particle systems. Chem. Engng Sci. 116, 645656.CrossRefGoogle Scholar
Dopazo, C. 1994 Probability Density Function Approach for a Turbulent Axisymmetric Heated Jet Centreline Evolution (ed. Libby, P. A. & Williams, F. A.), pp. 375474. Academic Press.Google Scholar
Eaton, J. K. & Fessler, J. R. 1994 Preferential concentration of particles by turbulence. Intl J. Multiphase Flow 20, 169209.CrossRefGoogle Scholar
Ertesvåg, I. S. & Magnussen, B. F. 2000 The eddy dissipation turbulence energy cascade model. Combust. Sci. Technol. 159, 213235.CrossRefGoogle Scholar
Gao, J., Xu, C., Lin, S. & Yang, G. 2004 Advanced model for turbulent gas–solid flow and reaction in FCC riser reactors. AIChE J. 45, 10951113.CrossRefGoogle Scholar
Hara, T., Muto, M., Kitano, T., Kurose, R. & Komori, S. 2015 Direct numerical simulation of a pulverized coal jet flame employing a global volatile matter reaction scheme based on detailed reaction mechanism. Combust. Flame 162, 43914407.CrossRefGoogle Scholar
Haugen, N. E. L. & Brandenburg, A. 2006 Hydrodynamic and hydromagnetic energy spectra from large eddy simulations. Phys. Fluids 18, 075106.CrossRefGoogle Scholar
Haugen, N. E. L., Kleeorin, N., Rogachevskii, I. & Brandenburg, A. 2012 Detection of turbulent thermal diffusion of particles in numerical simulations. Phys. Fluids 24, 075106.CrossRefGoogle Scholar
Jones, W. P. & Launder, B. E. 1972 The prediction of laminarization with a two-equation model of turbulence. Intl J. Heat Mass Transfer 15, 301314.CrossRefGoogle Scholar
Klimanek, A., Adamczyk, W., Katelbach-Wozniak, A., Wecel, G. & Szlek, A. 2015 Towards a hybrid Eulerian Lagrangian CFD modeling of coal gasification in a circulating fluidized bed reactor. Fuel 152, 131137.CrossRefGoogle Scholar
Kruger, J., Haugen, N. E. L., Løvas, T. & Mitra, D. 2017 The effect of turbulence on the reaction rate of particles with heterogeneous surface reactions. Proc. Combust. Inst. 36, 23333240.Google Scholar
Luo, K., Wang, H., Fan, J. & Yi, F. 2012 Direct numerical simulation of pulverized coal combustion in a hot vitiated co-flow. Energy Fuels 26, 61286136.CrossRefGoogle Scholar
Magnussen, B. F. & Hjertager, B. H. 1976 On mathematical models of turbulent combustion with special emphasis on soot formation and combustion. In 16th Symposium (International) on Combustion, pp. 719729. The Combustion Institute.Google Scholar
Pope, S. B. 2003 Turbulent Flows. Cambridge University Press.Google Scholar
Ranz, W. E. & Marshall, W. R. 1952 Evaporation from Drops. Chem. Engng Prog. 48, 141–146 and 173–180.Google Scholar
Schiller, L. & Naumann, A. 1933 Über die grundlegenden Berechnungen bei der Schwerkraftaufbereitung. Z. Verein. Deutsch. Ing. 77, 318320.Google Scholar
Silaen, A. & Wang, T. 2010 Effect of turbulence and devolatilization models on coal gasification simulation in an entrained-flow gasifier. Intl J. Heat Mass Transfer 53, 20742091.CrossRefGoogle Scholar
Squires, K. D. & Eaton, J. K. 1991 Measurements of particle dispersion obtained from direct numerical simulations of isotropic turbulence. J. Fluid Mech. 226, 135.CrossRefGoogle Scholar
Toschi, F. & Bodenschatz, E. 2009 Lagrangian properties of particles in turbulence. Annu. Rev. Fluid Mech. 41, 375404.CrossRefGoogle Scholar
Vascellari, M., Roberts, D. G., Hla, S. S., Harris, D. J. & Hasse, C. 2015 From laboratory-scale experiments to industrial-scale CFD simulations of entrained flow coal gasification. Fuel 152, 5873.CrossRefGoogle Scholar
Vascellari, M., Schulze, S., Nikrityuk, P., Safronov, D. & Hasse, C. 2014 Numerical simulation of pulverized coal MILD combustion using a new heterogeneous combustion submodel. Flow Turbul. Combust. 92, 319345.CrossRefGoogle Scholar
Wood, A. M., Hwang, W. & Eaton, J. K. 2005 Preferential concentration of particles in homogeneous and isotropic turbulence. Intl J. Multiphase Flow 31, 12201230.CrossRefGoogle Scholar
Zhang, Y., Wei, X.-L., Zhou, L.-X. & Sheng, H.-Z. 2005 Simulation of coal combustion by AUSM turbulence-chemistry char combustion model and a full two-fluid model. Fuel 84, 17981804.Google Scholar