Simulation of Binary Mixture Droplet Evaporation using VOF Methods

Similar documents
Performance Analysis for Natural Draught Cooling Tower & Chimney through Numerical Simulation

Numerical Investigation of the Flow Dynamics of a Supersonic Fluid Ejector

PERFORMANCE ANALYSIS OF NATURAL DRAFT WET COOLING TOWER AT OPTIMIZED INJECTION HEIGHT

Theory Comparison between Propane and Methane Combustion inside the Furnace

Abstract. Nomenclature. A Porosity function for momentum equations L Latent heat of melting (J/Kg) c Specific heat (J/kg-K) s Liquid fraction

Agenda. Background Validation studies. 3D application. Co-simulation. Summary. Espedal stratified flow. StatOil wavy-slug flow.

Analysis of the corrosion test process for heat exchangers in corrosion test chambers by CFD simulation

ME 239: Rocket Propulsion. Real Nozzles. J. M. Meyers, PhD

Liquid-Solid Phase Change Modeling Using Fluent. Anirudh and Joseph Lam 2002 Fluent Users Group Meeting

Mathematical Modelling of Drying Kinetics of Wheat in Electron Fired Fluidized Bed Drying System

Study of water falling film over horizontal drop shaped and inverted drop shaped tubes

ANSYS Combustion Analysis Solutions - Overview and Update

Modeling and experimental results of heavy oil injection into a high pressure entrained flow gasifier

Prediction of Pollutant Emissions from Industrial Furnaces Using Large Eddy Simulation

2D axial-symmetric model for fluid flow and heat transfer in the melting and resolidification of a vertical cylinder

A NOVEL TECHNIQUE FOR EXTRACTION OF GEOTHERMAL ENERGY FROM ABANDONED OIL WELLS

Optimization of abrasive waterjet nozzle design for precision and reduced wear using compressible multiphase CFD modelling

INVESTIGATION OF VOID REACTIVITY BEHAVIOUR IN RBMK REACTORS

Computer modelling of a convective steam superheater

Heat Storage Performance of a Honeycomb Ceramic Monolith

CFD Analysis of Pelton Runner

Combustion in anode baking furnaces: Comparison of two modeling approaches to predict variability

Splat formation in plasma-spray coating process*

VALIDATION OF A CFD MODEL IN RECTANGULAR SETTLING TANKS

Numerical Prediction of Turbulent Combustion Flows for 1700 C Class Gas Turbine Combustor

Modeling of HTPEM Fuel Cell Start-Up Process by Using Comsol Multiphysics

Assessment of Toxic Gas Dispersion using Phast and Panache

Deformation behavior of a liquid droplet impacting a solid surface

Modelling of the off-gas exit temperature and slag foam depth. of an Electric Arc Furnace

modeling of grain growth and coarsening in multi-component alloys

TECHNOLOGIES FOR APPLYING FLUIDS IN SEMICONDUCTOR PACKAGING

Numerical Simulation of Spray Cooling Gas with High Temperature and Velocity in Compressor Inter-Stage

FLUENT 6.3 Fuel Cell Modules Manual

Modeling of Transport Phenomena in Metal Foaming

CFD MODELLING OF MACRO-SEGREGATION AND SHRINKAGE IN LARGE DIAMETER STEEL ROLL CASTINGS: A COMPARISON ON SEN AND DLP TECHNIQUES

OPTIMIZATION OF PURE WATER JET PROCESS PARAMETERS USING FE MODELLING

Droplet formation mechanisms in metallurgical processes

APPLICATIONS OF A DYNAMIC THREE-DIMENSIONAL NUMERICAL MODEL FOR BOREHOLE HEAT EXCHANGERS. M. He, S.J. Rees, L. Shao

Multiphase Flow Dynamics 4

5 th OpenFOAM Workshop, Gothenburg, Sweden, June 21-24th, 2010 Using OpenFOAM for Tunnel Ventilation Design

An Investigation of Oxide Layer Impact on Heat Transfer in a Fuel Element of the MARIA Reactor

Heat transfer modelling of slot jet impinging on an inclined plate

HEAT TRANSFER AND FLUID FLOW IN STATIONARY GTA WELDING OF γ-tial BASED ALLOYS: EFFECT OF THERMOCAPILLARY FLOW

ScienceDirect. CFD Analysis of a Kerosene Fuel Tank to Reduce Liquid Sloshing

COOLING EFFECT ENHANCEMENT IN MAGNETRON SPUTTERING SYSTEM

Principles of Engineering Thermodynamics. 8th Edition SI Version

Generation of small batch high quality metal powder

Flow and Heat Transfer Characteristics in High Porosity Metal Foams

Numerical study of the influence of injection/production well perforation location on CO 2 -EGS system

CEE 452/652. Week 12, Lecture 1 Cyclones. Dr. Dave DuBois Division of Atmospheric Sciences, Desert Research Institute

A Modeling of Biomass Fast Pyrolysis using CFD in a fluidized bed reactor

The formation of oscillation marks in continuous casting of steel

Rapid DNA amplification in a capillary tube by natural convection with a single isothermal heater

Modeling 2D and 3D of Hybrid Laser Nd:Yag - MIG Welding Processes

Hideout of Sodium Phosphates in Steam Generator Crevices

Univ. Prof. Dr.-Ing. habil. K. Görner. Numerical Calculation and Optimisation of a large Municipal Solid Waste Incinerator Plant

Computational and Analytical Methods in AM: Linking Process to Microstructure

Using STAR-CCM+ for Research and Teaching at the Chair of Chemical & Process Engineering

Low-Grade Waste Heat Recovery for Power Production using an Absorption-Rankine Cycle

Multiphase Flow in the Subsurface - Flow of a Light Nonaqueous Phase Liquid (LNAPL)

Objective and Methodology

Thermal performance of a closed wet cooling tower for chilled ceilings: measurement and CFD simulation

The Reduced Pumping Power Requirements from Increasing the Injection Well Fluid Density

Analysis of Side Sluice in Trapezoidal Channel

Numerical Backstepping for Diameter Control of Silicon Ingots in the Czochralski Process

Revue des Energies Renouvelables Spécial ICT3-MENA Bou Ismail (2015) Numerical study of a single effect ejector-absorption cooling system

Heat Pump Efficiencies simulated in Aspen HYSYS and Aspen Plus

Liquid metal expulsion during laser spot welding of 304 stainless steel

Numerical prediction of temperature and density distributions in selective laser sintering processes

CFD MODELLING OF PULVERIZED COAL COMBUSTION IN A ROTARY LIME KILN

Validation studies of CFD codes on hydrogen combustion

Local Single- and Two-Phase Heat Transfer from an Impinging Cross-Shaped Jet

Simulation of Engine Flow with Swirl Using Re-Stress Turbulence Model in KIVA Code

FLUID FLOW - PUMPS. Discharge Section. Section. Two main types of pumps: Positive Displacement pumps Centrifugal pumps.

Investigation of the Flow Field inside a Drainage System: Gully - Pipe - Manhole

OPTIMIZED DESIGN FOR HEAVY MOUND VENTURI

Mathematical modelling of high velocity oxygen fuel thermal spraying of nanocrystalline materials: an overview

CONTROL VOLUME ANALYSIS USING ENERGY. By Ertanto Vetra

Computer Models For Fire and Smoke

S.P. YIM Korea Atomic Energy Research Institute P.O.Box 150, Yusong, Daejon, Republic of Korea

Quenching steels with gas jet arrays

Evaluation of Stability for Ecological Revetment Method with Stone Mattress and Vegetation Mound Using ANSYS Fluent

CFD modelling of argon stirred ladle. FIMECC Advanced Melt Metallurgy (AMMe) -project

Numerical Simulation of Heat Transfer in Porous Metals for Cooling Applications

CFD ANALYSIS OF MINI CHANNEL HEAT EXCHANGER USING WATER AS A WORKING FLUID

The Influence of Hydrodynamics on the Spread of. Pollutants in the Confluence of two Rivers

A three-dimensional numerical model of air pollutant dispersion

ASME PTC Flow Measurement

2008 International ANSYS Conference

CFD/FEM Based Analysis Framework for Wind Effects on Tall Buildings in Urban Areas

Simulation of the Flow in a Packed-Bed with and without a Static Mixer by Using CFD Technique

Chapter 7 Mass Transfer

INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET)

Air-Sea Gas Exchange

Characterization of Coal and Biomass. Conversion Behaviors in Advanced Energy Systems

Thermal Management of Densely-packed EV Battery Set

Performance Analysis of Shell and Tube Heat Exchanger Using Miscible System

NUMERICAL MODEL FOR PREDICTION OF CRACKS IN CONCRETE STRUCTURES

Parameters of the Atmospheric Air in the Dimensioning of Industrial Cooling Tower

Transcription:

Peter Keller and Christian Hasse Department of Energy Process Engineering and Chemical Engineering TU Bergakademie Freiberg Simulation of Binary Mixture using VOF Methods June 14, 2011 6 th OpenFOAM R Workshop, PennState University, USA, 2011

Overview Motivation Physics and mathematics Validation Case setup Results Conclusion and outlook TU Bergakademie Freiberg 1

Motivation I Fig. 1: Fuel injection and ignition, source: BMW Main aim: simulation of multicomponent fuel combustion Whole process too complex to validate Analysis of single steps from fuel injection until flame expansion Fig. 2: Simulation of n-heptane combustion Validation of atomization of open jets computationally very expensive Almost no experimental data for multicomponent fuel evaporation Mathematical validation just with simplifications possible TU Bergakademie Freiberg 2

Motivation II First checks of atomization behaviour depending on nozzle design turbulent inflow necessary Studies on secondary breakup of n-heptane droplets Validation of single component fuel droplet evaporation in dependence on temperature below and above boiling temperature Combination of atomization, evaporation and chemical reaction (described in [Keller et al.]) Current work: binary mixture evaporation implemented in OpenFOAM R using Volume of Fluid (VOF) approach Further implementations due to multicomponent mixtures and Cantera-/flamelet-coupling in preparation TU Bergakademie Freiberg 3

Physics and Mathematics I Basic solver: intermixingfoam - interface capture of 3 incompressible fluids (miscible liquids) using VOF approach Source code extended due to gas mixture, source terms for evaporation, enthalpy equation, mixing laws for ideal gases and liquids VOF special: scalar transport equation for liquid volume fraction Volume-of-fluid equation (liquid tracking): α = 0, if gas + (αu) = 0, t with α (0, 1), if interface = 1, if liquid TU Bergakademie Freiberg 4

Physics and Mathematics II - Modified Conservation Equations Momentum equation (original) (ρu) t with surface tension force F s = σ m κˆn. + (ρuu) = µ [ u + ( u) T ] +ρg p F s VOF-equations (in original version for gas phase α 1 and first liquid phase α 2 ) α 2 t + (φ α 2 ) = D 23 α 2 Ṡα 2 α 3 t + (φ α 3 ) = D 32 α 3 Ṡα 3 α 1 = 1 α 2 α 3 with volumetric source terms Ṡα 2 and Ṡα 3 and special OpenFOAM-fluxes φ α2 and φ α3 TU Bergakademie Freiberg 5

Physics and Mathematics III - Modified Conservation Equations Species transport equations Y G1 t Y G2 t + (Y G1 u) = D G1 Y G1 + ṠY G1 + (Y G2 u) = D G2 Y G2 + ṠY G2 Y G3 = 1 Y G1 Y G2 with mass related evaporation source terms ṠY G1 and ṠY G2 Enthalpy equation with evaporation source ṠH h s t + (h λ su) = h s + ρc ṠH p TU Bergakademie Freiberg 6

Physics and Mathematics IV - Modified Conservation Equations Mass conservation (until now still incompressible) with volume balance term Ṡp u = Ṡp Source terms (exemplary): [ ] DG1 ρ G M C1 Ṡ YG1 = δ 1 Y G1 ( κ) 1 Y G1 ρ G1 M G [ ] λ M C1 +(1 δ 1 ) T ( κ) ρ G1 H v,1 M G [ ] DG2 ρ G M C2 Ṡ YG2 = δ 2 Y G2 ( κ) 1 Y G2 ρ G2 M G [ ] λ M C2 +(1 δ 2 ) T ( κ) ρ G2 H v,1 M G TU Bergakademie Freiberg 7

Physics and Mathematics VI - Gradients Discretization of gradients according Y Gi = Y G i,sat Y Gi δx and T = T T boil,i δx Fig. 3: Gradient calculation Calculation of saturation mass fractions using Raoult s law and Wagner equation according: Y Gi,sat = M C 1 p i,sat M G p ln p i,sat = T c,i p c T X L i (A i ( 1 T T c,i +C i ( 1 T T c,i ) + B i ( 1 T T c,i ) 3 + D i ( 1 T T c,i ) 1.5 ) 6 ) TU Bergakademie Freiberg 8

Physics and Mathematics VII - PLIC Fig. 4: 3D PLIC, source: [Gueyffier et al.] Distance δx of mass center of gas and surface calculated using piecewise-linear interface calculation PLIC According Gueyffier et al. volume of liquid in cell 1 3 V = d 3 H(d n j dj)(d n j dj) 3 6n x n y n z j=1 3 + H(d d max + n j dj)(d d max + n j dj) 3 j=1 with d = n x x + n y y + n z z, surface normal n = n x n y n z, cell lengths dx l = dy dz With mass center of gas phase (x s, y s, z s ) determination of distance: δx = x x x s + n y y s + n z z s d n 2 x + n 2 y + n 2 z TU Bergakademie Freiberg 9

Physics and Mathematics VIII - Species and Mixture Properties Determination of substance-specific properties according: Watson equation (evaporation enthalpies), Fuller relation (gas mixture diffusion coefficients), Tyn/Calus method (liquid mixture diffusion coefficient), Hugill/Welsenes equation (surface tension),... different polynomials (thermal conductivity, viscosities,... ) and NASA-polynomials (heat capacities, enthalpies) Example: Tyn/Calus Dij ( m 2 = 8.93 10 12 10 6 M ) 1/3 ( C j 10 6 M C i /s ρ Lj ρ Li ) 1/6 ( ) 0.6 Pj T (10 3 η Lj ) 1 P i and hence D AB,L = (D AB) XB (D BA) X A TU Bergakademie Freiberg 10

Validation - Single Component I Axisymmetric mesh with 160000 cells Initial diameter D = 100 µm Different initial liquid temperatures Tl 1 = 300 K and Tl 2 = 320 K Inflow temperature T = 350 K, Reynolds number Re < 1 Validation done using D 2 -law (see [Turns(2000)]) with dd 2 dt K = 8ρD AB ρ l = K ( ) 1 YA, ln 1 Y A,sat TU Bergakademie Freiberg 11

Validation - Single Component II Single component T d 0 =300 K Single component T d 0 =320 K 1 0.9998 Simulation T S =310 K analytics 1 0.9998 Simulation T S =311 K analytics 0.9996 0.9996 Diameter mm 2 /mm 0 2 0.9994 0.9992 0.999 Diameter mm 2 /mm 0 2 0.9994 0.9992 0.999 0.9988 0.9988 0.9986 0.9986 0.9984 0 5e-05 0.0001 0.00015 0.0002 0.00025 0.0003 0.9984 0 5e-05 0.0001 0.00015 0.0002 0.00025 0.0003 Time in s Time in s Fig. 5: Validation single component evaporation: Tl 1 = 300 K Fig. 6: Validation single component evaporation: Tl 2 = 320 K Good agreement between analytics and simulation results Droplet heating/cooling from different initial state to almost equal surface temperature TU Bergakademie Freiberg 12

Validation - Binary Mixture I Same mesh and diameter as before Initial liquid temperature T l = 300 K Inflow temperature T = 350 K, Reynolds number Re < 1 Droplet composition: α 2 = 0.8, α 3 = 0.2 Expanding to multicomponent mixtures, D 2 -law reads: dd 2 dt = K K = 8ρ ρ l J j=1 D jm ln 1 J j=1 Y vap,j, 1 J j=1 Y vap,j,sat TU Bergakademie Freiberg 13

Validation - Binary Mixture II 1 0.9995 Simulation T S =307 K analytics 0.999 Diameter mm 2 /mm 0 2 0.9985 0.998 0.9975 0.997 0.9965 0.996 0.9955 0.995 0 5e-05 0.0001 0.00015 0.0002 0.00025 0.0003 Time in s Fig. 7: Validation binary mixture evaporation: T 1 l = 300 K TU Bergakademie Freiberg 14

Case Setup Fig. 8: Scheme of 2D-geometry Same configuration for 2D- and 3D-cases (cylindrical shape) 2D mesh resolution: 500 200 cells 3D mesh resolution: 2Mio. cells Droplet: 2D 300, 3D 3000 cells CFL=0.2 Parameter variations due to temperature and composition influence as well as impact of Weber number W e = ρ gu 2 rel d σ 3 3D- and 16 2D-simulations (see table next slide) TU Bergakademie Freiberg 15

Case Setup - Parameter Variation List, D=1 mm # Species Dim U in [m/s] Y L1 T [K] ρ G [kg/m 3 ] σ [ m/s 2 ] We Re 1 octane 2D 1.0 1 350 1.064 0.0206 0.05 53 2 octane 2D 4.54 1 350 1.064 0.0206 1 240 3 octane 2D 70 1 350 1.064 0.0206 250 3700 4 heptane+decane 2D 4.54 0.3 320 1.164 0.02223 1 280 5 heptane+decane 2D 4.54 0.3 350 1.064 0.02223 1 240 6 heptane+decane 2D 4.54 0.3 400 0.93 0.02223 0.9 190 7 heptane+decane 2D 4.54 0.3 600 0.6208 0.02223 0.6 95 8 hexane+dodecane 2D 4.54 0.3 350 1.064 0.0232 1 240 9 hexane+dodecane 2D 4.54 0.5 600 0.6208 0.0219 0.6 95 10 hexane+dodecane 2D 70 0.8 350 1.064 0.0197 265 3700 11 hexane+dodecane 2D 220 0.5 600 0.6208 0.0219 1370 11600 12 heptane+decane 2D 70 0.3 350 1.064 0.0223 230 3700 13 heptane+decane 2D 70 0.5 350 1.064 0.0216 240 3700 14 heptane+decane 2D 70 0.8 350 1.064 0.0205 250 3700 15 heptane+decane 2D 70 0.5 600 0.6208 0.0216 140 1470 16 heptane+decane 2D 70 0.8 600 0.6208 0.0205 150 1470 17 heptane+decane 3D 70 0.5 350 1.064 0.0216 240 3700 18 heptane+decane 3D 4.54 0.5 600 0.6208 0.0216 0.6 95 19 hexane+dodecane 3D 70 0.8 350 1.064 0.0197 265 3700 Tab. 1: Parameter list TU Bergakademie Freiberg 16

Results I - Weber Number Fig. 9: Case 7, We=0.5 Fig. 10: Case 5, We=1 Fig. 11: Case 15, We=140 Fig. 12: Case 11, We=1370 TU Bergakademie Freiberg 17

Results II - Weber Number Base Cases n-octane 1 Base Case We=0.1 Base Case We=1 Base Case We=70 Diameter mm 2 /mm 0 2 0.999 0.998 0.997 # Species We 1 octane 0.05 2 octane 1 3 octane 250 0.996 Tab. 2: Parameter list 0.995 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 Time in s Fig. 13: Base cases, Weber number variation Reference cases with n-octane (same solver - similar properties) Higher Weber number evaporation faster due to surface enlargement and transport of vapor TU Bergakademie Freiberg 18

Results III - Weber Number Weber Number Variation Diameter mm 2 /mm 0 2 1 0.998 0.996 0.994 Case 5 Case 11 Case 12 Case 15 # Species We 5 heptane+decane 1 11 hexane+dodecane 1370 12 heptane+decane 230 15 heptane+decane 140 0.992 Tab. 3: Parameter list 0.99 0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.01 Time in s Fig. 14: Weber number variation Same as before for higher Weber numbers Temperature difference (case 12 and 15) higher evaporation rate at beginning and earlier achievement of saturation concentration at surface TU Bergakademie Freiberg 19

Results IV - Temperature Temperature Variation Diameter mm 2 /mm 0 2 1 0.998 0.996 0.994 Base Case We=1 Case 4 Case 5 Case 6 Case 7 # Species T in [K] 2 octane 350 4 heptane+decane 320 5 heptane+decane 350 6 heptane+decane 400 7 heptane+decane 600 0.992 0.99 0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.01 Time in s Tab. 4: Parameter list Fig. 15: Inflow temperature variation Before breakup single component case (T base = T 5 ) slower than binary ones With breakup and surface enlargement acceleration of evaporation of single component case higher TU Bergakademie Freiberg 20

Results V - Composition Composition Variation 1 Base Case We=70 Case 10 Case 12 Case 14 Diameter mm 2 /mm 0 2 0.998 0.996 0.994 # Species Y L1 3 octane 1 10 hexane+dodecane 0.8 12 heptane+decane 0.3 14 heptane+decane 0.8 0.992 0.99 0 0.0001 0.0002 0.0003 0.0004 0.0005 Time in s Tab. 5: Parameter list Fig. 16: Composition variation Evaporation rate strongly dependent on composition Higher liquid concentration of high volatile components (case 10 n-hexane, case 14 n-heptane) higher evaporation rate TU Bergakademie Freiberg 21

Results IV - 2D Case 3D Case 3D-2D Comparison 1 3D Case 17 Case 13 Diameter mm 2 /mm 0 2 0.998 0.996 0.994 0.992 0.99 0 0.0001 0.0002 0.0003 0.0004 0.0005 Time in s Fig. 17: 3D Case (17) Fig. 18: Comparison 2D-3D (13-17) Similar results for 2D- and 3D-case Transient behaviour and temperature drop observable TU Bergakademie Freiberg 22

Conclusion Conclusions New VOF-solver implemented to solve for binary mixture evaporation and breakup Validation done for single component and binary mixture droplet evaporation Differences shown between single component and binary mixture droplet evaporation caused by temperature differences, composition and inflow velocity Outlook Generalization of solver due to multicomponent mixtures Coupling with flamlet library and hence chemical reactions Coupling with Cantera to compute species properties of gas phase TU Bergakademie Freiberg 23

References [Keller et al.] Keller, P.; Nikrityuk, P.A.; Meyer, B.; Müller-Hagedorn, M., "Numerical Simulation of Evaporating Droplets with Chemical Reactions using a Volume of Fluid Method", 7 th International Conference on Multiphase Flows, 2010 [Gueyffier et al.] Gueyffier, D.; Li, J.; Nadim, A.; Scardovelli, R.; Zaleski, S., "Volume-of-Fluid Interface Tracking with Smoothed Surface Stress Methods for Three-Dimensional Flows", Journal of Computational Physics 152, p. 423-456, 1999 [Turns(2000)] Turns, S.R., "An Introduction to Combustion - Concepts and Applications", McGraw-Hill Higher Education, 2000 TU Bergakademie Freiberg 24

Acknowledgement The research has been funded by the Bavarian Science Foundation in the project WiDiKO - Wirkkette Direkteingespritzter Kraftstoffe im Ottomotor (project number NP:275) and by the Federal Ministry of Education and Research of Germany in framework of Virtuhcon (project number 040201030). Thanks to Bernhard Gschaider for his valuable comments and collaboration. Thank you for your attention! TU Bergakademie Freiberg 25