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Formation and break-up of rigid agglomerates in turbulent channel and pipe flows

Published online by Cambridge University Press:  25 October 2018

K. C. J. Schutte Open the ORCID record for K. C. J. Schutte [Opens in a new window] ,
L. M. Portela ,
A. Twerda  and
R. A. W. M. Henkes
K. C. J. Schutte
Affiliation:
Department of Chemical Engineering, Delft University of Technology, Post Office Box 5, 2600 AA Delft, The Netherlands
L. M. Portela
Affiliation:
Department of Chemical Engineering, Delft University of Technology, Post Office Box 5, 2600 AA Delft, The Netherlands
A. Twerda
Affiliation:
Process & Energy Department, Delft University of Technology, Post Office Box 5, 2600 AA Delft, The Netherlands TNO, Post Office Box 6012, 2600 JA Delft, The Netherlands
R. A. W. M. Henkes*
Affiliation:
Process & Energy Department, Delft University of Technology, Post Office Box 5, 2600 AA Delft, The Netherlands
*
†Email address for correspondence: [email protected]
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Abstract

We have developed and applied an Eulerian–Lagrangian model for the transport, formation, break-up, deposition and re-entrainment of particle agglomerates. In this paper, we focus on agglomeration and break-up. Simulations were carried out to investigate what changes in the turbulent flow are inflicted by the presence of the agglomerates. Also, the dependence of the properties of the agglomerates on the Reynolds number of the flow and on the strength of the bonds between the primary particles is studied. The presence of the agglomerates attenuates the turbulence and thereby lowers the Reynolds stresses. As a result, the flow rate increases at constant pressure drop when agglomerates are formed (up to a certain dimension). If the agglomerates surpass this dimension, long-distance viscosity effects become dominant and a flow rate decrease occurs. The characteristics of the agglomerates are largely insensitive to the Reynolds number, provided the flow is turbulent. The agglomerates have an open and porous structure, and a fractal dimension of 1.8–2.3. Their mean mass scales exponentially with the strength of the internal bonds. Contrary to assumptions that are typically made in engineering models in the literature, agglomerates do not preferentially break into two fragments of similar size.

JFM classification

Multiphase and Particle-laden Flows: Multiphase and Particle-laden Flows Multiphase and Particle-laden Flows: Particle/fluid flow
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 857 , 25 December 2018 , pp. 539 - 561
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Copyright
© 2018 Cambridge University Press 

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References

Babler, M. U. 2008 A collision efficiency model for flow-induced coagulation of fractal aggregates. AIChE J. 54, 1748–1760.Google Scholar
Babler, M. U., Biferale, L., Brandt, L., Feudel, U., Guseva, K., Lanotte, A. S., Marchioli, C., Picano, F., Sardina, G., Soldati, A. & Toschi, F. 2015 Numerical simulations of aggregate breakup in bounded and unbounded turbulent flows. J. Fluid Mech. 766, 104–128.Google Scholar
Balachandar, S. & Eaton, J. K. 2010 Turbulent dispersed multiphase flow. Annu. Rev. Fluid Mech. 42, 111–133.Google Scholar
Boersma, B. J.1997 Electromagnetic effects in cylindrical pipe flow. PhD thesis, Delft University of Technology.Google Scholar
de Bona, J., Lanotte, A. S. & Vanni, M. 2014 Internal stresses and breakup of rigid isostatic aggregates in homogeneous and isotropic turbulence. J. Fluid Mech. 755, 365–396.Google Scholar
Brunk, B. K., Koch, D. L. & Lion, L. W. 1998 Turbulent coagulation of colloidal particles. J. Fluid Mech. 364, 81–113.Google Scholar
Chen, D. & Doi, M. 1999 Microstructure and viscosity of aggregating colloids under strong shearing force. J. Colloid Interface Sci. 212, 286–292.Google Scholar
Chen, M., Kontomaris, K. & McLaughlin, J. B. 1999 Direct numerical simulation of droplet collisions in a turbulent channel flow. Part I: collision algorithm. Int J. Multiphase Flow 24, 1079–1103.Google Scholar
Crowe, C. T., Sommerfeld, M. & Tsuji, Y. 1997 Multiphase Flows with Droplets and Particles. CRC Press.Google Scholar
Derksen, J. J. 2008 Flow-induced forces in sphere doublets. J. Fluid Mech. 608, 337–356.Google Scholar
Derksen, J. J. 2012 Direct numerical simulations of aggregation of monosized spherical particles in homogeneous isotropic turbulence. AIChE J. 58, 2589–2600.Google Scholar
Dizaji, F. F. & Marshall, J. S. 2016 An accelerated stochastic vortex structure method for particle collision and agglomeration in homogeneous turbulence. Phys. Fluids 28, 113301.Google Scholar
Eggels, J. G. M.1994 Direct and large eddy simulation of turbulent flow in a cylindrical pipe geometry. PhD thesis, Delft University of Technology.Google Scholar
Ernst, M., Dietzel, M. & Sommerfeld, M. 2013 A lattice Boltzmann method for simulating transport and agglomeration of resolved particles. Acta Mech. 224, 2425–2449.Google Scholar
Flesch, J. C., Spicer, P. T. & Pratsinis, S. E. 1999 Laminar and turbulent shear-induced flocculation of fractal aggregates. AIChE J. 45, 1114–1124.Google Scholar
Gastaldi, A. & Vanni, M. 2011 The distribution of stresses in rigid fractal-like aggregates in a uniform flow field. J. Colloid Interface Sci. 357, 18–30.Google Scholar
van Haarlem, B. A.2000 The dynamics of particles and droplets in atmospheric turbulence: A numerical study. PhD thesis, Delft University of Technology.Google Scholar
Johnson, K. L., Kendall, K. & Roberts, A. D. 1971 Surface energy and the contact of elastic solids. Proc. R. Soc. A 324, 301–313.Google Scholar
El Khoury, G. K., Schlatter, P., Noorani, A., Fischer, P. F., Brethouwer, G. & Johansson, A. V. 2013 Direct numerical simulation of turbulent pipe flow at moderately high Reynolds numbers. Flow Turbul. Combust. 91, 475–495.Google Scholar
Lazzari, S., Nicoud, L., Jaquet, B., Lattuada, M. & Morbidelli, M. 2016 Fractal-like structures in colloid science. Adv. Colloid Interface Sci. 235, 1–13.Google Scholar
Li, Y., McLaughlin, J. B., Kontomatis, K. & Portela, L. 2001 Numerical simulation of particle-laden turbulent channel flow. Phys. Fluids 13, 2957–2967.Google Scholar
Mäkinen, J. T. T. 2005 Particle accretion and dissipation simulator: collisional aggregation of icy particles. Icarus 177, 269–279.Google Scholar
Marchioli, C., Soldati, A., Kuerten, J. G. M., Arcen, B., Tanière, A., Goldensoph, G., Squires, K. D., Cargnelutti, M. F. & Portela, L. M. 2008 Statistics of particle dispersion in direct numerical simulations of wall-bounded turbulence: results of an international collaborative benchmark test. Int J. Multiphase Flow 34, 879–893.Google Scholar
Meakin, P. & Jullien, R. 1988 The effects of restructuring on the geometry of clusters formed by diffusion-limited, ballistic, and reaction-limited cluster–cluster aggregation. J. Chem. Phys. 89, 246–250.Google Scholar
Moser, R. D., Kim, J. & Mansour, N. N. 1999 Direct Numerical Simulation of turbulent channel flow up to Re 𝜏 = 590. Phys. Fluids 11, 943–945.Google Scholar
Paschkewitz, J. S., Dubief, Y., Dimitropoulos, C. D., Shaqfeh, E. S. G. & Moin, P. 2004 Numerical simulation of turbulent drag reduction using rigid fibres. J. Fluid Mech. 518, 281–317.Google Scholar
Portela, L. M., Cota, P. & Oliemans, R. V. A. 2002 Numerical study of the near-wall behaviour of particles in turbulent pipe flows. Powder Technol. 125, 149–157.Google Scholar
Portela, L. M. & Oliemans, R. V. A. 2003 Eulerian–Lagrangian DNS/LES of particle–turbulence interactions in wall-bounded flows. Int J. Numer. Methods Fluids 43, 1045–1065.Google Scholar
Pourquié, M. J. B. M.1994 Large-eddy simulation of a turbulent jet. PhD thesis, Delft University of Technology.Google Scholar
Ptasinski, P. K., Nieuwstadt, F. T. M., van den Brule, B. H. A. A. & Hulsen, M. A. 2001 Experiments in turbulent pipe flow with polymer additives at maximum drag reduction. Flow Turbul. Combust. 66, 159–182.Google Scholar
Reade, W. C. & Collins, L. R. 2000 A numerical study of the particle size distribution of an aerosol undergoing turbulent coagulation. J. Fluid Mech. 415, 45–64.Google Scholar
Richardson, D. C. 1995 A self-consistent numerical treatment of fractal aggregate dynamics. Icarus 115, 320–335.Google Scholar
Schutte, K. C. J.2016 A hydrodynamic perspective on the formation of asphaltene deposits. PhD thesis, Delft University of Technology.Google Scholar
Sureshkumar, R., Beris, A. N. & Handler, R. A. 1998 Direct numerical simulation of the turbulent channel flow of a polymer solution. Phys. Fluids 9, 743–755.Google Scholar
Zinchenko, A. Z. & Davis, R. H. 2014 Growth of multiparticle aggregates in sedimenting suspensions. J. Fluid Mech. 742, 577–617.Google Scholar
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