Abstract
The multicomponent model and the effective diffusivity model are well established diffusion models for numerical simulation of single-phase flows consisting of several components but are seldom used for two-phase flows so far. In this paper, a specific numerical model for interfacial mass transfer by means of a continuous single-field concentration formulation is combined with the multicomponent model and effective diffusivity model and is validated for multicomponent mass transfer. For this purpose, several test cases for one-dimensional physical or reactive mass transfer of ternary mixtures are considered. The numerical results are compared with analytical or numerical solutions of the Maxell-Stefan equations and/or experimental data. The composition-dependent elements of the diffusivity matrix of the multicomponent and effective diffusivity model are found to substantially differ for non-dilute conditions. The species mole fraction or concentration profiles computed with both diffusion models are, however, for all test cases very similar and in good agreement with the analytical/numerical solutions or measurements. For practical computations, the effective diffusivity model is recommended due to its simplicity and lower computational costs.
Similar content being viewed by others
Abbreviations
- c i :
-
Molar concentration of species i (mol m−3)
- c ref :
-
Reference concentration (mol m−3)
- c t :
-
Total molar concentration of mixture (mol m−3)
- C :
-
Concentration normalized by c ref (−)
- D i , j :
-
Fick diffusion coefficient in the GFL diffusivity matrix (m2 s−1)
- Ð i , j :
-
Maxwell-Stefan diffusion coefficient for species pair i and j (m2 s−1)
- D i , eff :
-
Effective diffusivity of species i (m2 s−1)
- f :
-
Volume fraction of liquid phase (−)
- H i :
-
Henry number of species i (−)
- h :
-
Length of computational domain (m)
- j i , j i :
-
Diffusive molar flux relative to molar-average velocity (mol m−2 s−1)
- \( {j}_i^{\mathrm{V}},\kern0.5em {\mathbf{j}}_i^{\mathrm{V}} \) :
-
Diffusive molar flux relative to volume-average velocity (mol m−2 s−1)
- J :
-
Species vector of diffusive molar fluxes, J = (j 1, j 2, …, j n − 1)T (mol m−2 s−1)
- k :
-
Reaction constant (m s−1)
- m :
-
Time step index (−)
- M i :
-
Molecular weight of species i (g mol−1)
- n :
-
Number of species (−)
- N :
-
Molar flux (mol m−2 s−1)
- Pe i , j :
-
Binary Péclet number (−)
- Pe ref :
-
Reference Péclet number (−)
- r i :
-
Reactive source term of species i in Eq. (5) (mol m−3 s−1)
- \( {r}_i^{\mathrm{V}} \) :
-
Reactive source term of species i in Eq. (6) (mol m−3 s−1)
- \( {\dot{s}}_i \) :
-
Reaction rate (mol m−2 s−1)
- \( {\dot{S}}_i \) :
-
Non-dimensional reaction rate (−)
- t :
-
Time (s)
- u i :
-
Partial velocity of species i (m s−1)
- u , u :
-
Molar-average velocity (m s−1)
- u V , u V :
-
Volume-average velocity (m s−1)
- u M , u M :
-
Mass-average velocity (m s−1)
- \( {\overline{V}}_i \) :
-
Partial molar volume of species i (m3 mol−1)
- \( {\overline{V}}_{\mathrm{t}} \) :
-
Total molar volume of mixture, \( {\overline{V}}_{\mathrm{t}}=1/{c}_{\mathrm{t}} \) (m3 mol−1)
- x i :
-
Mole fraction of species i (−)
- z :
-
Coordinate of one-dimensional problem (m)
- Z :
-
Non-dimensional coordinate, Z = z/L ref (−)
- δ :
-
Degree of dilution (−)
- ν :
-
Stoichiometric coefficient (−)
- ρ i :
-
Partial mass density of species i (kg m−3)
- ρ t :
-
Total mass density (kg m−3)
- θ :
-
Non-dimensional time (−)
- ω i :
-
Mass fraction of species i (−)
- eff:
-
Effective
- i :
-
Species index
- int:
-
Interface
- G:
-
Gas phase
- L:
-
Liquid phase
- m:
-
Two-phase mixture quantity
- ref:
-
Reference
- t:
-
Total
- 0:
-
Initial value
- eq:
-
Equilibrium
- M:
-
Mass average
- V:
-
Volume average
- CCDM:
-
Continuous concentration diffusivity model
- EDM:
-
Effective diffusivity model
- GFL:
-
Generalized Fick law
- MCM:
-
Multicomponent model
- MS:
-
Maxwell-Stefan
- NESM:
-
Non-equilibrium stage model
References
Tryggvason G, Scardovelli R, Zaleski S (2011) Direct numerical simulations of gas-liquid multiphase flows. Cambridge University Press, Cambridge
Wörner M (2012) Numerical modeling of multiphase flows in microfluidics and micro process engineering: a review of methods and applications. Microfluid Nanofluid 12:841–886
Günther A, Jhunjhunwala M, Thalmann M, Schmidt MA, Jensen KF (2005) Micromixing of miscible liquids in segmented gas-liquid flow. Langmuir 21:1547–1555
Yue J, Luo LG, Gonthier Y, Chen GW, Yuan Q (2009) An experimental study of air-water Taylor flow and mass transfer inside square microchannels. Chem Eng Sci 64:3697–3708
Haase S, Bauer T (2011) New method for simultaneous measurement of hydrodynamics and reaction rates in a mini-channel with Taylor flow. Chem Eng J 176–177:65–74
Hirt CW, Nichols BD (1981) Volume of fluid (VOF) method for the dynamics of free boundaries. J Comput Phys 39:201–225
Sussman M, Smereka P, Osher S (1994) A Level Set Approach for Computing Solutions to Incompressible Two-Phase Flow. J Comput Phys 114:146–159
Unverdi SO, Tryggvason G (1992) A front-tracking method for viscous, incompressible, multi-fluid flows. J Comput Phys 100:25–37
Bothe D, Kröger M, Alke A, Warnecke H-J (2009) VOF-based simulation of reactive mass transfer across deformable interfaces. Prog Comput Fluid Dy 9:325–331
Bothe D, Kröger M, Warnecke H-J (2011) A VOF-Based Conservative Method for the Simulation of Reactive Mass Transfer from Rising Bubbles. Fluid Dyn Mater Proc 7:303–316
Kenig EY, Ganguli AA, Atmakidis T, Chasanis P (2011) A novel method to capture mass transfer phenomena at free fluid-fluid interfaces. Chem Eng Process 50:68–76
Bothe D, Fleckenstein S (2013) A Volume-of-Fluid-based method for mass transfer processes at fluid particles. Chem Eng Sci 101:283–302
Eisenschmidt K, Ertl M, Gomaa H, Kieffer-Roth C, Meister C, Rauschenberger P, Reitzle M, Schlottke K, Weigand B (2016) Direct numerical simulations for multiphase flows: An overview of the multiphase code FS3D. Appl Math Comput 272:508–517
Haroun Y, Legendre D, Raynal L (2010) Volume of fluid method for interfacial reactive mass transfer: Application to stable liquid film. Chem Eng Sci 65:2896–2909
Marschall H, Hinterberger K, Schuler C, Habla F, Hinrichsen O (2012) Numerical simulation of species transfer across fluid interfaces in free-surface flows using OpenFOAM. Chem Eng Sci 78:111–127
Deising D, Marschall H, Bothe D (2016) A unified single-field model framework for Volume-Of-Fluid simulations of interfacial species transfer applied to bubbly flows. Chem Eng Sci 139:173–195
Petera J, Weatherley LR (2001) Modelling of mass transfer from falling droplets. Chem Eng Sci 56:4929–4947
Bothe D, Koebe M, Wielage K, Prüss J, Warnecke H-J (2004) Direct numerical simulation of mass transfer between rising gas bubbles and water. In: Sommerfeld M (ed) Bubbly flows Analysis, modelling and calculation. Springer, Berlin, pp 159–174
Yang C, Mao Z-S (2005) Numerical simulation of interphase mass transfer with the level set approach. Chem Eng Sci 60:2643–2660
Onea A, Wörner M, Cacuci DG (2009) A qualitative computational study of mass transfer in upward bubble train flow through square and rectangular mini-channels. Chem Eng Sci 64:1416–1435
Hayashi K, Tomiyama A (2011) Interface Tracking Simulation of Mass Transfer from a Dissolving Bubble. J Comput Multiphase Flow 3:247–262
Banerjee R (2007) A numerical study of combined heat and mass transfer in an inclined channel using the VOF multiphase model. Numer Heat Transfer, Part A 52:163–183
Schlottke J, Weigand B (2008) Direct numerical simulation of evaporating droplets. J Comput Phys 227:5215–5237
Hassanvand A, Hashemabadi SH (2011) Direct numerical simulation of interphase mass transfer in gas-liquid multiphase systems. Int Commun Heat Mass Transfer 38:943–950
Bird RB, Stewart WE, Lightfoot EN (2002) Transport phenomena, 2nd edn. John Wiley, New York
Taylor R, Krishna R (1993) Multicomponent mass transfer. Wiley, New York
Bird RB, Klingenberg DJ (2013) Multicomponent diffusion-A brief review. Adv Water Resour 62:238–242
Curtiss CF, Bird RB (1999) Multicomponent diffusion. Ind Eng Chem Res 38:2515–2522
Matuszak D, Donohue MD (2005) Inversion of multicomponent diffusion equations. Chem Eng Sci 60:4359–4367
Merk HJ (1959) The macroscopic equations for simultaneous heat and mass transfer in isotropic, continuous and closed systems. Appl Sci Res 8:73–99
Gandhi KS (2012) Use of Fick's law and Maxwell-Stefan equations in computation of multicomponent diffusion. AIChE J 58:3601–3605
Nauman EB, Savoca J (2001) An engineering approach to an unsolved problem in multicomponent diffusion. AIChE J 47:1016–1021
Mazumder S (2006) Critical assessment of the stability and convergence of the equations of multi-component diffusion. J Comput Phys 212:383–392
Rehfeldt S, Stichlmair J (2007) Measurement and calculation of multicomponent diffusion coefficients in liquids. Fluid Phase Equilibr 256:99–104
Toor HL (1964) Solution of the Linearized Equations of Multicomponent Mass Transfer: I. AIChE J 10:448–455
Toor HL (1964) Solution of the Linearized Equations of Multicomponent Mass Transfer: II. Matrix Methods. AIChE J 10:460–465
Padoin N, Dal'Toe ATO, Rangel LP, Ropelato K, Soares C (2014) Heat and mass transfer modeling for multicomponent multiphase flow with CFD. Int J Heat Mass Transf 73:239–249
Wilke CR (1950) Diffusional Properties of Multicomponent Gases. Chem Eng Prog 46:95–104
Kumar A, Mazumder S (2008) Assessment of various diffusion models for the prediction of heterogeneous combustion in monolith tubes. Comput Chem Eng 32:1482–1493
Lutz AE, Kee RJ, Grcar JF, Rupley FM (1997) OPPDIF: A Fortran program for computing opposed-flow diffusion flames. Sandia National Labs, Livermore SAND-96-8243
Warnatz J, Maas U, Dibble RW (2006) Combustion: physical and chemical fundamentals, modeling and simulation, experiments, pollutant formation, 4th edn. Springer, Berlin, New York
Kee RJ, Coltrin ME, Glarborg P (2003) Chemically reacting flow: theory and practice. Wiley-Interscience, Hoboken
Hayes RE, Liu B, Moxom R, Votsmeier M (2004) The effect of washcoat geometry on mass transfer in monolith reactors. Chem Eng Sci 59:3169–3181
Karadeniz H, Karakaya C, Tischer S, Deutschmann O (2013) Numerical modeling of stagnation-flows on porous catalytic surfaces: CO oxidation on Rh/Al2O3. Chem Eng Sci 104:899–907
Salmi T, Warna J (1991) Modeling of Catalytic Packed-Bed Reactors – Comparison of Different Diffusion-Models. Comput Chem Eng 15:715–727
Kee RJ, Dixon-Lewis G, Warnatz J, Coltrin ME, Miller JA (1986) A FORTRAN computer code package for the evaluation of gas-phase, multicomponent transport properties. Sandia National Labs, Livermore SAND86-8246
Desilets M, Proulx P, Soucy G (1997) Modeling of multicomponent diffusion in high temperature flows. Int J Heat Mass Transf 40:4273–4278
Kenig EY, Kholpanov LP (1992) Simultaneous Mass and Heat-Transfer with Reactions in a Multicomponent, Laminar, Falling Liquid-Film. Chem Eng J Biochem Eng J 49:119–126
Kenig EY, Butzmann F, Kucka L, Gorak A (2000) Comparison of numerical and analytical solutions of a multicomponent reaction-mass-transfer problem in terms of the film model. Chem Eng Sci 55:1483–1496
Kenig EY, Schneider R, Gorak A (2001) Multicomponent unsteady-state film model: a general analytical solution to the linearized diffusion-reaction problem. Chem Eng J 83:85–94
Chasanis P, Brass M, Kenig EY (2010) Investigation of multicomponent mass transfer in liquid-liquid extraction systems at microscale. Int J Heat Mass Transf 53:3758–3763
Banerjee R (2008) Turbulent conjugate heat and mass transfer from the surface of a binary mixture of ethanol/iso-octane in a countercurrent stratified two-phase flow system. Int J Heat Mass Transf 51:5958–5974
Haelssig JB, Tremblay AY, Thibault J, Etemad SG (2010) Direct numerical simulation of interphase heat and mass transfer in multicomponent vapour-liquid flows. Int J Heat Mass Transf 53:3947–3960
Cui XT, Li XG, Sui H, Li H (2012) Computational fluid dynamics simulations of direct contact heat and mass transfer of a multicomponent two-phase film flow in an inclined channel at sub-atmospheric pressure. Int J Heat Mass Transf 55:5808–5818
Poling BE, Prausnitz JM, O'Connell JP (2001) The properties of gases and liquids, 5th edn. McGraw-Hill, New York
Dal'Toe ATO, Padoin N, Ropelato K, Soares C (2015) Cross diffusion effects in the interfacial mass and heat transfer of multicomponent droplets. Int J Heat Mass Transf 85:830–840
Sabisch W (2000) Dreidimensionale numerische Simulation der Dynamik von aufsteigenden Einzelblasen und Blasenschwärmen mit einer Volume-of-Fluid-Methode. Forschungszentrum Karlsruhe Wissenschaftliche Berichte, FZKA 6478, Karlsruhe
Sabisch W, Wörner M, Grötzbach G, Cacuci DG (2001) Three-dimensional simulation of rising individual bubbles and swarms of bubbles by a volume-of-fluid method. Chem Ing Tech 73:368–373
Kececi S, Wörner M, Onea A, Soyhan HS (2009) Recirculation time and liquid slug mass transfer in co-current upward and downward Taylor flow. Catal Today 147S:S125–S131
Öztaskin MC, Wörner M, Soyhan HS (2009) Numerical investigation of the stability of bubble train flow in a square minichannel. Phys Fluids 21:042108. https://doi.org/10.1063/1.3101146
Patankar SV (1980) Numerical heat transfer and fluid flow Hemisphere. Pub. Corp. McGraw-Hill, Washington
Davidson MR, Rudman M (2002) Volume-of-fluid calculation of heat or mass transfer across deforming interfaces in two-fluid flow. Numer Heat Transfer, Part B 41:291–308
Carty R, Schrodt T (1975) Concentration Profiles in Ternary Gaseous Diffusion. Ind Eng Chem Fundam 14:276–278
Newman J (2009) Stefan-Maxwell mass transport. Chem Eng Sci 64:4796–4803
Deutschmann O, Tischer S, Correa C, Chatterjee J, Kleditzsch S, Janardhanan V, Mladenov N, Minh HD, Karadeniz H, Hettel M (2014) DETCHEM Software package, 2.5 ed, www.detchem.de, Karlsruhe
Irandoust S, Ertle S, Andersson B (1992) Gas-Liquid Mass-Transfer in Taylor Flow through a Capillary. Can J Chem Eng 70:115–119
Crank J (1975) The mathematics of diffusion, 2d edn. Clarendon Press, Oxford
Krishnamurthy R, Taylor R (1985) A Nonequilibrium Stage Model of Multicomponent Separation Processes. Part I: Model Description and Method of Solution. AIChE J 31:449–456
Hiller C, Buck C, Ehlers C, Fieg G (2010) Nonequilibrium stage modelling of dividing wall columns and experimental validation. Heat Mass Transf 46:1209–1220
Kenig E, Gorak A (1995) A Film Model-Based Approach for Simulation of Multicomponent Reactive Separation. Chem Eng Process 34:97–103
Cussler EL (2009) Diffusion: mass transfer in fluid systems, 3rd edn. Cambridge University Press, Cambridge
Sander R (2015) Compilation of Henry's law constants (version 4.0) for water as solvent. Atmos Chem Phys 15:4399–4981
Chasanis P, Lautenschleger A, Kenig EY (2010) Numerical investigation of carbon dioxide absorption in a falling-film micro-contactor. Chem Eng Sci 65:1125–1133
Machado RM (2007) Fundamentals of Mass Transfer and Kinetics for the Hydrogenation of Nitrobenzene to Aniline. ALR Application Note, Mettler-Toledo AutoChem. Inc, Columbia
Acknowledgements
We gratefully acknowledge the funding of this project by Helmholtz Energy Alliance “Energy Efficient Chemical Multiphase Processes” (HA-E-0004) and thank the Steinbeis GmbH & Co. KG für Technologietransfer (STZ 240 Reaktive Strömung) for a cost-free academic license of DETCHEM™.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Appendices
Appendix 1. Numerical solution of Maxwell-Stefan eqs
A classical model for describing diffusion in multicomponent systems is the Maxwell-Stefan diffusion, see e.g. [26]. At constant temperature and pressure, the total concentration and the binary diffusion coefficients are constant, and the driving forces of the Maxwell-Stefan diffusion are the gradients of mole fractions. For the one-dimensional problems considered here, the Maxwell-Stefan equations for ideal mixtures have the form
To obtain the species distribution from the molar fluxes, the first order spatial derivative is discretized by a forward finite difference so that Eq. (29) is discretized at position k as
At the left wall (z = 0), fixed mole fractions are specified as boundary conditions and 40 nodes are used for the Stefan-tube example of Section 3.1.1.
Appendix 2. Numerical solution of non-equilibrium stage model (NESM)
Kenig et al. [70] suggested an analytical model for two-phase mass transfer in a steady state, which is based on the non-equilibrium stage model [26]. In the NESM, the reactor is divided into several stages. Between the stages, different kinds of fluxes (due to feeding, production and consumption) are transferred. Kenig et al. [70] provided the stage equation for the two-phase mass transfer with a heterogeneous model for each phase. The equations for species i in stage j for gas and liquid phases are
Here, \( {V}_{\mathrm{G},i}^j \) and \( {V}_{L,i}^j \) denotes the molar flow rate to stage j with side stream, and r G and r L are the ratio of side stream to inter-stage flow. The second terms in Eq. (31) and Eq. (32) denote molar flow rates to stage j + 1. The third terms represent the molar flow rates by additional feed, and the fourth terms represent the mass transfer across the gas-liquid interface (with interfacial area \( {a}_{\mathrm{int}}^j \)). The fifth term, which appears only in the liquid phase equation, is the rate of heterogeneous reaction at the surface (with surface area \( {a}_{\mathrm{r}}^j \)).
For the test cases presented in section 3.2, side streams and additional feeds to the stages are neglected so that r G = r L = 0 and \( {V}_{\mathrm{FG},i}^j={V}_{\mathrm{FL},i}^j=0 \). Furthermore, the one-dimensional domain is divided into a number of neighboring stages so that Eq. (31) and Eq. (32) simplify to three types of equations. For stages containing one phase only it is, depending on the phase, either
For the stage with the gas-liquid interface it is
while for the stage with the reactive surface it is
For the present one-dimensional problems, the interfacial area (\( {a}_{\mathrm{int}}^j \)) and surface area of reaction (\( {a}_{\mathrm{r}}^j \)) are assumed to be identical so that the latter equations simplify to
and for the stage at the right wall
These equations turn out to be the same as the flux balance equation. The solution procedure is, therefore, similar as for the flux balance equation by finite difference method. The solution of this elliptic problem is obtained by an iterative method with 21 stages including one stage at the middle of the domain (Z = 0.5) with the gas-liquid interface, and one stage at the right reactive wall (Z = 1).
Rights and permissions
About this article
Cite this article
Woo, M., Wörner, M., Tischer, S. et al. Validation of a numerical method for interface-resolving simulation of multicomponent gas-liquid mass transfer and evaluation of multicomponent diffusion models. Heat Mass Transfer 54, 697–713 (2018). https://doi.org/10.1007/s00231-017-2145-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00231-017-2145-x