Experimental and Numerical Analysis of Gas-Liquid Flow on Distillation Trays Authors: Henry França Meier Dirceu Noriler
Summary State of Art Objectives this wor Experimental Setup Numerical analysis Model Validation Conclusions
State of Art Oil Industries Hydrocarbon fractionating process Equilibrium and Nonequilibrium stage model Macroscopic Models (90 century) Now - CFD Models
State of Art (CFD Models) Bubble Columns: Boisson and Malin (1996) Euler-Euler Model (Non-Drag Forces) Delnoij et al. (1997) - Euler-Lagrange Model; Solichin and Eigenberger (1999) 2D and 3D Models; Pfleger and Becer (2001) Experimental versus CFD Model; Michele and Hempel (2002) - Three-Phase Model; Krishna, van Baten, Urseanu e Ellenberger (1999, 2001) Two Regime of Bubble Flow Three Phase Model;
State of Art (CFD Models) Distillation Columns Liu et al. (2000, 2004, 2005) 2D Monophase model; van Baten and Krishna (2000) 3D Two-Phase Model; Gesit et al. (2003) - 3D Two-Phase Model Commercial Scale; Soares et al. (2002) and Noriler (2004) Homogeneous Model versus Heterogeneous Model; Noriler (2008) Thermal Fluid Dynamics Model Noriler (2007) Mass, Energy and Momentum Coupled Model
State of Art (Experimental) Based on Bennett et al. (1983) e Cowell (1979) wors, the pressure drop in sieve tray is compound by 3 components: Liquid Height: Dry tray: Superficial tension:
Our contributions By CFDOIL 1st CFD Worshop to thr Oil Industry: 2D Monophase model and 3D Homogeneous Two-Phase Model CFD OIL 2005: 3D Homogeneous Two-Phase Model with energy balance CFD OIL 2006: 3D Homogeneous Two-Phase Model with mass and energy balance Now CFD OIL 2006: Experimental analysis
Objective The mains objectives of this wor are: To develop a experimental wor to provide data for validation the models; To execute a numerical analysis and to compare the results with experimental results; To predict the efficiency of the distillation sieve tray.
Experimental Setup
66 holes with 6 mm in diameter. The perforated area is 2.26% based on bubble area. Hi=0.040 m H=0.750 m W=0.234 m D=0.350 m hw= 0.060 m Lp=0.260 m
Image of apparatus
Data acquisition scheme
Image of Image of sensors
Signal integration
Software acquisition
Experimental movie
Statistics treatments V S =0.193 m/s; Q L /W=2.4 x 10-3 m 3 s -1 m -1
a and cv Constants Dry tray contribution
Pressure Drop Components. Q L /W=2.4 x 10-3 m 3 s -1 m -1
Clear Liquid Height and Center Point Clear Liquid Height Liquid Rate Dependence. V s =0.348 m/s Superficial Gás Velocity Dependence. Q L /W=2.4 x 10-3 m 3 s -1 m -1
Comparison with Bennett et al. (1983) correlation
Numerical Analysis The model consider the Inter-phase transfer term for momentum equation ( this is used approach that was developed by rishna et al.(2000)): ( ) β β β β ρ = v v v v M D D C d f 4 3 With and Bennett et al. (1983) correlation for average volume fraction of liquid 2 p D 1 gd 3 4 C β β ρ ρ ρ = v v average S f V β β = v v B S A Q V β = ρ ρ ρ = β β β 0.91 S average V 12.55 exp 1 f
Numerical Methods Grid Top viewer Grid Side viewer
Clear liquid height as a function of superficial velocity Q L /W=2.4 x 10-3 m 3 s -1 m -1
Qualitative model Validation
Qualitative Validation Q L /W 2.14 x 10-3 m 3 s -1 m -1
Quantitative Validation Clear Liquid Height. Q L /W=2,14 x 10-3 m 3 s -1 m -1
Quantitative Validation Numerical and Experimental Data Relation. Q L /W=2,14 x 10-3 m 3 s -1 m -1
Efficiency Prediction
Mathematical Modeling Continuity equation: t ( f ρ ) + ( f ρ v ) 0 = Momentum equation: t With, ( ) ( ) [ ( )] ' eff T f ρ v + f ρ v v = f p + f µ v + v µ eff t =µ + µ + f ρ g+ F j
Mathematical Modeling Energy equation: t λ eff Mass equation: t D eff ( fρh ) + ( fρvh ) = ( fλ T) Qj =λ µ + Pr t t e eff ( f ρ y ) + ( f v y ) + ( f ρ D ( y )) eff A = D A A µ + Pr eff t m A A A Y Aj
Mathematical Modeling Where, F j inter - phase transfer term of momentum equation, and Q Y j Aj inter - phase transfer term of energy equation inter - phase transfer term of mass equation.
Turbulence- standard -ε: Constitutive Equation ( ) ( ) ε ρ = σ µ + µ ρ + ρ P f f f t t v Where, and ( ) ( ) ε ε ρ ε = ε σ µ + µ ε ρ + ε ρ 2 1 t C C P f f f t v µ ε = µ t t C ( ) ( ) T t P + µ = v v v
Inter-phase transfer term for momentum equation: With ( ) j j D j D j C d f 4 3 v v v v F ρ = Constitutive Equation and Bennett et al. (1983) correlation for average volume fraction of liquid 2 j p j D 1 gd 3 4 C v v ρ ρ ρ = average j S j f V = v v B j S A Q V = ρ ρ ρ = 0,91 j j S average j V 12.55 exp 1 f
Constitutive Equation Inter-phase transfer term for energy equation Q j = h j A j ( T T ) j with A = j 6f d P Modelo γ-φ UNIQUAC -γ IDEAL -φ Inter-phase transfer term for energy equation Antoine - P Sat and Y Aj A j ( ) c e c 2.6 10 = jajρ yaj ya with j = 0. 25 µ 43 = A 0,3 h B ( V ρ ) S j 20 H σ L ρ j ρ H F 5 (Zuiderweg (1982))
Simulation Results Momentum Balances Distribution of average liquid holdup in x-y plane along height of dispersion. Source: Zuiderweg, 1982 0.12 Height Along Dispersion (m) 0.10 0.08 0.06 0.04 Source: Bennett et al., 1983 0.02 0.00 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Liquid Holdup
Simulation Results Energy Balances b) Temperature 82,11 ºC 82.3 liquid temperature (ºC) 82.2 82.1 82.0 b) Temperature 82,32 ºC 81.9 0.00 0.03 0.06 0.09 0.12 0.15 0.18 0.21 0.24 Liquid Inlet Distance (m) Weir
0.766 Liquid Phase 0.765 0.764 Chemical Species Balances Ethanol Mass Fraction 0.763 0.762 0.761 0.760 0.759 Ethanol Mass Fraction 0.760 Average Ethanol Mass Fraction in the Liquid Phase = 0.0756 0.755 0.750 0.745 0.740 0.735 0.730 Quasi-Steady State Ethanol Mass Fraction 0.758 0.757 0.8474 0.8472 0.8470 0.8468 0.8466 0.8464 0.8462 Average Ethanol Mass Fraction = 0.7605 87.0 87.5 88.0 88.5 89.0 Time (s) Vapour Phase Average Ethanol Mass Fraction = 0.8465 0.725 0.8460 0.8458 56 60 64 68 72 76 80 84 88 Time (s) 87.0 87.5 88.0 88.5 89.0 Time (s)
Snapshots of the properties
Tray Efficiency 70 68 66 Tray Efficiency = 64.16 % Murphree Efficiency (%) 64 62 60 58 56 54 52 50 1 2 3 4 5 6 7 8 9 10 Murphree (1925) Effi = y y out eq West et al. (1952) y y in in Point Efficiency based on Murphree Efficiency Point
Conclusions A experimental setup was built to provide data to validate the CFD models; the proposed model was validated qualitatively and quantitatively; It is possible to predict the Tray Efficiency by CFD Techniques. The Tray efficiency for ethanol/water mixture is about 64 % for distillation tray studied; The CFD tools presented and discussed in this wor mae possible to now better the turbulent gas-liquid flow on a sieve plate of distillation columns and they can be used to optimize design and operating condition of such processes.