1. Mechanistic Modeling and CFD Simulations of Oil-Water Dispersions in Separation Components Mechanistic Modeling and CFD Simulations of Oil-Water Dispersions in Separation Components TUSTP 2003 by Carlos F. Torres May 20, 2003 by Carlos F. Torres May 20, 2003

2.  Background  Objectives  Particle Tracking Model  Preliminary Results  Universal Dispersion Model TopicsTopics

3.  Knowledge of particle motion and phase distribution will enhance performance evaluation of separation equipment  TUSTP has used the Eulerian-Lagrangian technique to design and analyze performance of separation devices such as GLCC, LLCC and LLHC  Existing models carry out simulations considering mainly the following forces acting on a particle: drag and buoyancy  Additionally, these models assume particle local equilibrium BackgroundBackground

4.  The general objectives of this study are to develop models capable of characterizing hydrodynamics of multiphase dispersion flow in separations and piping components  Initially, study focuses on dilute and dense dispersed flow  Develop a mechanistic model for calculating droplet motion, considering the different acting forces  Determine dispersed phase void fraction  Validate and extend the three way coupling approach proposed by Gomez 2001 ObjectivesObjectives

5.  General approach  Simplified approach  Future improvements Particle Tracking Model

6. Particle Tracking: General Approach  Gomez 2001 presented a new Eulerian – Lagrangian mechanistic model:  Local equilibrium assumed for dispersed phase  Forces used: drag, lift, body force, added mass and pressure gradient  Model is one way coupling between continuous and dispersed phase, considering variation of interfacial area

7. Lagrangian Equation  Forces on particle  Effects of continuous phase turbulence on particle:  Behzadi et al (2001) presented an averaging approach for the effects of fluid turbulence on particles  Iliopoulos et al. (2003) presented a stochastic model for the effects of turbulence in dispersed flow

8. Particle Tracking: Simplified Approach  Modifications of Gomez model (2001):  Forces considered: drag, lift and body force  Main goal is calculation of particle trajectory  Parametric technique (function of time) allows determination of particle’s residence time (integration 2 nd order accuracy)  Particles are spherical and non-deformable, particle to particle interaction not considered (dilute dispersion)  One way coupling  3D solution developed for Cartesian and Cylindrical coordinate systems

9. Modified Gomez Model  Particle Position  Forces on Particle

10. Particle Tracking: Future Improvements  Extend model capability to include:  Added mass force  Pressure gradient force (hydrodynamic)  Fluid turbulent effects  Particle transients effect  Develop mechanistic model for estimation of void fraction using stochastic approach  Explore limits of dilute flow assumption, and extend to dense flow

11. Preliminary Results  Particle Tracking in Pipe Flow  Particle Tracking in Stratified Flow  Particle Tracking in Conventional Separators

12. Particle Tracking: Pipe Flow Mixing Length Velocity Profile

13.  = 0 o, d = 5in, V cont = 0.01 m/s. Water Continuous (1000 kg/m 3, 1cp). Dispersed phase Oil (850 kg/m 3 ), dp = 100 microns Particle Tracking: Pipe Flow

14. Shoham and Taitel (1984)  = 0 o, d = 3in, Uls = 0.1 m/s, Ugs = 1.0 m/s Air Water system at 25  C and 1 atm. Particle Tracking: Stratified Flow

15. Particle Tracking: Conventional Separators

17. Particle Residence Time = 2.63 s Particle Density = 2500 kg/m 3 Particle Diameter = 500 micron

18. Particle Tracking: Conventional Separators Particle Residence Time = 2.362 s Particle Density = 2500 kg/m 3 Particle Diameter = 500 micron

19. Universal Dispersion Model  Gomez Model (2001)  The Eulerian field is known (average velocities, turbulent kinetic energy and energy dissipation)  Solve Lagrangian field using the proposed equation, to calculate slip velocity within flow field  Solve diffusion equation using slip velocity information, to predict void fraction distribution  Calculate bubble or droplet diameter using Eulerian turbulent quantities and void fraction distribution  Repeat non-linear process until convergence is reached

20. Phase Coupling Model  Definition of Phase Coupling  One-way Coupling: Fluid flow affects particle while there is no reverse effect.  Two-way Coupling: fluid flow affects particle and vice versa.  Four-way Coupling:Additionally from above, there are hydrodynamic interactions between particles, and turbulent particle collisions.  Three-way Coupling

21. Phase Coupling Model  Dispersed phase momentum equation (average)  Continuous phase momentum equation (N- S Equation)  Particle Source Term, MPso is estimated by coupling mass and momentum balances over control volume.

22. Two-way Coupling: Solution Scheme  PSI – Cell technique, Crowe et al. (1977) Huber & Sommerfelt (1997). Air continuous Phase.  = 0 o, d = 80 mm, V = 24 m/s, Dispersed phase  d = 2500 kg/m 3 d p = 40 micron

23. Model Potential LLCC Dispersion of Oil in Water with Water Layer at the Bottom V m = 0.6 m/s W.C = 67%

24. Questions ? ?