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The effect of turbulence on mass transfer rates between inertial polydisperse particles and fluid

Published online by Cambridge University Press:  15 July 2019

Ewa Karchniwy Open the ORCID record for Ewa Karchniwy [Opens in a new window] ,
Adam Klimanek Open the ORCID record for Adam Klimanek [Opens in a new window]  and
Nils Erland L. Haugen Open the ORCID record for Nils Erland L. Haugen [Opens in a new window]
Ewa Karchniwy*
Affiliation:
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Kolbjørn Hejes vei 1B, 7491 Trondheim, Norway Institute of Thermal Technology, Silesian University of Technology, Konarskiego 22, 44-100 Gliwice, Poland
Adam Klimanek
Affiliation:
Institute of Thermal Technology, Silesian University of Technology, Konarskiego 22, 44-100 Gliwice, Poland
Nils Erland L. Haugen
Affiliation:
Department of Energy and Process Engineering, Norwegian University of Science and Technology, Kolbjørn Hejes vei 1B, 7491 Trondheim, Norway SINTEF Energi AS, Sem Saelands vei 11, 7034 Trondheim, Norway
*
†Email address for correspondence: ewa.karchniwy@polsl.pl
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Abstract

The current work investigates how turbulence affects the mass transfer rate between inertial particles and fluid in a dilute, polydisperse particle system. Direct numerical simulations are performed in which all scales of turbulence are fully resolved and particles are represented in a Lagrangian reference frame. The results show that, similarly to a monodisperse system, the mass transfer rate between particles and fluid decreases as a result of particle clustering. This occurs when the flow time scale (based on the turbulence integral scale) is long relative to the chemical time scale, and is strongest when the particle time scale is one order of magnitude smaller than the flow time scale (i.e. the Stokes number is around 0.1). It is also found that for larger solid mass fractions, the clustering of the heavier particles is enhanced by the effect of drag force from the particles on the fluid (momentum back-reactions or two-way coupling). In particular, when two-way coupling is accounted for, locations of particles of different sizes are much more correlated, which leads to a stronger effect of clustering, and thus a greater reduction of the particle–fluid mass transfer rate.

JFM classification

Reacting Flows: Combustion Reacting Flows: Turbulent reacting flows
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 874 , 10 September 2019 , pp. 1147 - 1168
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Copyright
© 2019 Cambridge University Press 

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References

Adamczyk, W. P., Bialecki, R. A., Ditaranto, M., Gladysz, P., Haugen, N. E. L., Katelbach-Wozniak, A., Klimanek, A., Sladek, S., Szlek, A. & Wecel, G. 2017 CFD modeling and thermodynamic analysis of a concept of a mild-oxy combustion large scale pulverized coal boiler. Energy 140, 1305–1315.Google Scholar
Adamczyk, W. P., Kozołub, P., Klimanek, A., Białecki, R. A., Andrzejczyk, M. & Klajny, M. 2015 Numerical simulations of the industrial circulating fluidized bed boiler under air- and oxy-fuel combustion. Appl. Therm. Engng 87, 127–136.Google Scholar
Al-Abbas, A. H., Naser, J. & Dodds, D. 2012 CFD modelling of air-fired and oxy-fuel combustion in a large-scale furnace at Loy Yang A brown coal power station. Fuel 102, 646–665.Google Scholar
Baker, L., Frankel, A., Mani, A. & Coletti, F. 2017 Coherent clusters of inertial particles in homogeneous turbulence. J. Fluid Mech. 833, 364–398.Google Scholar
Baxter, L. L. & Smith, P. J. 1993 Turbulent dispersion of particles: the STP model. Energy Fuels 7, 852–859.Google Scholar
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 (8), 084502.Google Scholar
Brosh, T. & Chakraborty, N. 2014 Effects of equivalence ratio and turbulent velocity fluctuation on early stages of pulverized coal combustion following localized ignition: a direct numerical simulation analysis. Energy Fuels 28, 6077–6088.Google 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, 50–62.Google Scholar
Calzavarini, E., Kerscher, M., Lohse, D. & Toschi, F. 2008 Dimensionality and morphology of particle and bubble clusters in turbulent flow. J. Fluid Mech. 607, 13–24.Google Scholar
Choi, C. R. & Kim, C. N. 2009 Numerical investigation on the flow, combustion and NOx emission characteristics in a 500 MWe tangentially fired pulverized-coal boiler. Fuel 88, 1720–1731.Google Scholar
Eaton, J. K. & Fessler, J. R. 1994 Preferential concentration of particles by turbulence. Intl J. Multiphase Flow 20, 169–209.Google Scholar
Graham, D. I. 1996 An improved eddy interaction model for numerical simulation of turbulent particle dispersion. J. Fluids Engng 118, 819–823.Google Scholar
Gubba, S. R., Ingham, D. B., Larsen, K. J., Ma, L., Pourkashanian, M., Tan, H. Z., Williams, A. & Zhou, H. 2012 Numerical modelling of the co-firing of pulverised coal and straw in a 300 MWe tangentially fired boiler. Fuel Process. Technol. 104, 181–188.Google 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, 4391–4407.Google Scholar
Haugen, N. E. L., Krüger, J., Mitra, D. & Løvås, T. 2018 The effect of turbulence on mass transfer rates of small inertial particles with surface reactions. J. Fluid Mech. 836, 932–951.Google 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.Google Scholar
Haugen, N. E. L., Mitchell, R. E. & Tilghman, M. B. 2015 A comprehensive model for char particle conversion in environments containing O2 and CO2 . Combust. Flame 162, 1455–1463.Google Scholar
Haugen, N. E. L., Tilghman, M. B. & Mitchell, R. E. 2014 The conversion mode of a porous carbon particle during oxidation and gasification. Combust. Flame 161, 612–619.Google Scholar
Krüger, J., Haugen, N. E. L., Mitra, D. & Løvås, T. 2017a The effect of turbulent clustering on particle reactivity. Proc. Combust. Inst. 36, 2333–2340.Google Scholar
Krüger, J., Haugen, N. E. L. & Løvås, T. 2017b Correlation effects between turbulence and the conversion rate of pulverized char particles. Combust. Flame 185, 160–172.Google Scholar
Launder, B. E. & Spalding, D. B. 1974 The numerical computation of turbulent flows. Comput. Meth. Appl. Mech. Engng 3, 269–289.Google Scholar
Luo, K., Bai, Y., Jin, T., Qiu, K. & Fan, J. 2017 Direct numerical simulation study on the stabilization mechanism of a turbulent lifted pulverized coal jet flame in a heated coflow. Energy Fuels 31, 8742–8757.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, 6128–6136.Google Scholar
Magnussen, B. F. & Hjertager, B. H. 1977 On mathematical modeling of turbulent combustion with special emphasis on soot formation and combustion. Symp. Combust. 16 (1), 719–729.Google Scholar
Mitra, D., Haugen, N. E. L. & Rogachevskii, I. 2018 Turbulent Soret effect. Eur. Phys. J. 133, 35.Google Scholar
Monchaux, R., Bourgoin, M. & Cartellier, A. 2012 Analyzing preferential concentration and clustering of inertial particles in turbulence. Intl J. Multiphase Flow 40, 1–18.Google Scholar
Muto, M., Yuasa, K. & Kurose, R. 2017 Numerical simulation of ignition in pulverized coal combustion with detailed chemical reaction mechanism. Fuel 190, 136–144.Google Scholar
Pencil Code http://www.nordita.org/software/pencil-code/.Google Scholar
Pope, S. B. 1985 PDF methods for turbulent reactive flows. Prog. Energy Combust. Sci. 11, 119–192.Google Scholar
Pope, S. B.2000 Turbulent Flows, chap. 6, pp. 182–263. Cambridge University Press.Google Scholar
Ranz, W. E. & Marshall, W. R. 1952 Evaporation from drops. Parts I and II. Chem. Engng Prog. 48, 141–173.Google Scholar
Schiller, L. & Naumann, A. Z. 1933 Uber die grundlegenden berechungen bei der schwerkraftaufbereitung. Ver. Deut. Ing. 77, 318–320.Google Scholar
Toschi, F. & Bodenschatz, E. 2009 Lagrangian properties of particles in turbulence. Annu. Rev. Fluid Mech. 41, 375–404.Google Scholar
Wilcox, D. C. 1988 Reassessment of the scale-determining equation for advanced turbulence models. AIAA J. 26 (11), 1299–1310.Google Scholar
Yoshimoto, H. & Goto, S. 2007 Self-similar clustering of inertial particles in homogeneous turbulence. J. Fluid Mech. 577, 275–286.Google Scholar
Zimont, V., Polifke, W., Bettelini, M. & Weisenstein, W. 1998 An efficient computational model for premixed turbulent combustion at high Reynolds numbers based on a turbulent flame speed closure. Trans. ASME J. Engng Gas Turbines Power 120, 526–532.Google Scholar