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Research Papers: Multiphase Flows

Experimental and Simulated Studies of Oil/Water Fully Dispersed Flow in a Horizontal Pipe

[+] Author and Article Information
D. S. Santos

Department of Chemical Engineering,
Faculty of Sciences and Technology,
Chemical Process Engineering and Forest
Products Research Centre (CIEPQPF),
University of Coimbra,
Polo 2, Pinhal de Marrocos,
Coimbra 3030-290, Portugal;
CAPES Foundation,
Ministry of Education of Brazil,
Caixa Postal 250,
Brasília DF 70040-020, Brazil
e-mail: deividson@eq.uc.pt

P. M. Faia

Department of Electrical and
Computers Engineering,
Faculty of Sciences and Technology,
University of Coimbra,
Polo 2, Pinhal de Marrocos,
Coimbra 3030-290, Portugal
e-mail: faia@deec.uc.pt

F. A. P. Garcia

Department of Chemical Engineering,
Faculty of Sciences and Technology,
Chemical Process Engineering and Forest
Products Research Centre (CIEPQPF),
University of Coimbra,
Polo 2, Pinhal de Marrocos,
Coimbra 3030-290, Portugal
e-mail: fgarcia@eq.uc.pt

M. G. Rasteiro

Department of Chemical Engineering,
Faculty of Sciences and Technology,
Chemical Process Engineering and Forest
Products Research Centre (CIEPQPF),
University of Coimbra,
Polo 2, Pinhal de Marrocos,
Coimbra 3030-290, Portugal
e-mail: mgr@eq.uc.pt

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received December 5, 2018; final manuscript received April 9, 2019; published online May 23, 2019. Assoc. Editor: Kevin R. Anderson.

J. Fluids Eng 141(11), 111301 (May 23, 2019) (14 pages) Paper No: FE-18-1818; doi: 10.1115/1.4043498 History: Received December 05, 2018; Revised April 09, 2019

The flow of oil/water mixtures in a pipe can occur under different flow patterns. Additionally, being able to predict adequately pressure drop in such systems is of relevant importance to adequately design the conveying system. In this work, an experimental and numerical study of the fully dispersed flow regime of an oil/water mixture (liquid paraffin and water) in a horizontal pipe, with concentrations of the oil of 0.01, 0.13, and 0.22 v/v were developed. Experimentally, the values of pressure drop, flow photographs, and radial volumetric concentrations of the oil in the vertical diameter of the pipe cross section were collected. In addition, normalized conductivity values were obtained, in this case, for a cross section of the pipe where an electrical impedance tomography (EIT) ring was installed. Numerical studies were carried out in the comsolmultiphysics platform, using the Euler–Euler approach, coupled with the k–ε turbulence model. In the simulations, two equations for the calculation of the drag coefficient, Schiller–Neumann and Haider–Levenspiel, and three equations for mixture viscosity, Guth and Simba (1936), Brinkman (1952), and Pal (2000), were studied. The simulated data were validated with the experimental results of the pressure drop, good results having been obtained. The best fit occurred for the simulations that used the Schiller–Neumann equation for the calculation of the drag coefficient and the Pal (2000) equation for the mixture viscosity.

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Figures

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Fig. 1

Scheme of the closed-loop pipeline: (1) oil/water tank; (2) butterfly valve; (3) differential pressure transducer; (4) mixture injection pump; (5) Pt 100 temperature probe; (6) mixture flowmeter; (7) sampling probe; (8) acrylic box; (9) EIT electrode ring; (10) EIT acquisition system; (11) fluid inlet in the test section; and (12) 90 deg elbow

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Fig. 2

Microscopic images of the oil/water mixture with oil concentration of 0.22 v/v and velocity of the mixture of 1.3 m s−1 in the base of the pipe: (a) is the microscopic image and (b) is the size distribution of the droplets in the mixture. Ød is the droplet diameter.

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Fig. 3

Scheme of the geometry

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Fig. 4

Two-dimensional unstructured mesh used in simulations in 2D geometry (91,371 elements for the final mesh). L is the length, and R is the radius of the pipe.

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Fig. 5

Simulated radial velocity profiles for the mixture velocity of 2.6 m s−1 and oil concentrations of 0.01 v/v (a), 0.13 v/v (b), and 0.22 v/v (c). R is the radius of the pipe.

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Fig. 6

Pressure drop versus velocity of the mixture. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Guth and Simba (1936) equation.

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Fig. 7

Pressure drop versus velocity of the mixture. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Brinkman (1952) equation.

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Fig. 8

Pressure drop versus velocity of the mixture. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Pal (2000) equation.

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Fig. 9

Pressure drop versus velocity of the mixture. Drag coefficient calculated by the Haider–Levenspiel correlation and viscosity calculated by the Guth and Simba (1936) equation.

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Fig. 10

Pressure drop versus velocity of the mixture. Drag coefficient calculated by the Haider–Levenspiel correlation and viscosity calculated by the Pal (2000) equation.

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Fig. 11

Radial profile of the turbulent kinetic energy simulated by comsolmultiphysics. Velocity of the mixture of 0.9 m s−1 and volumetric concentration of the oil 0.01, 0.13, and 0.22. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Pal (2000) equation. R is the radius of the pipe.

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Fig. 12

Radial profile of the turbulent kinetic energy simulated by comsolmultiphysics. Velocity of the mixture of 2.6 m s−1 and volumetric concentration of the oil 0.01, 0.13, and 0.22. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Pal (2000) equation. R is the radius of the pipe.

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Fig. 13

Radial profile of turbulent dissipation rate simulated by comsolmultiphysics. Velocity of the mixture of 0.9 m s−1 and volumetric concentration of the oil 0.01, 0.13, and 0.22. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Pal (2000) equation. R is the radius of the pipe.

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Fig. 14

Radial profile of turbulent dissipation rate simulated by comsolmultiphysics. Velocity of the mixture of 2.6 m s−1 and volumetric concentration of the oil 0.01, 0.13, and 0.22. Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Pal (2000) equation. R is the radius of the pipe.

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Fig. 15

Flow photographs (left side) and simulated concentration patterns for a short length of pipe using comsolmultiphysics (right side). Velocity of the mixture 2.6 m s−1 and volumetric oil concentration of 0.01 (a), 0.13 (b), and 0.22 (c). Drag coefficient calculated by the Schiller–Neumann correlation and viscosity calculated by the Pal (2000) equation. L is the length, and R is the radius of pipe.

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Fig. 16

EIT images for the flows with the volumetric concentrations of the oil of 0.01 (a), 0.13 (b), and 0.22 (c) and velocity of the mixture of 2.6 m s−1

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Fig. 17

One-dimensional radial profiles of volumetric concentration for a velocity of the mixture of 0.9 m s−1 and for oil concentrations of 0.01 (a), 0.13 (b), and 0.22 (c). In the simulations, S1 corresponds to the Schiller–Neumann correlation and Pal (2000) equation used to calculate drag coefficient and viscosity, respectively, and S2 corresponds to the Haider–Levenspiel correlation and Pal (2000) equation to calculate drag coefficient and viscosity, respectively.

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Fig. 18

One-dimensional radial profiles of volumetric concentration for a velocity of the mixture of 1.5 m s−1 and for oil concentrations of 0.01 (a), 0.13 (b), and 0.22 (c). In the simulations, S1 corresponds to the Schiller–Neumann correlation and Pal (2000) equation used to calculate drag coefficient and viscosity, respectively, and S2 corresponds to the Haider–Levenspiel correlation and Pal (2000) equation to calculate drag coefficient and viscosity, respectively.

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Fig. 19

One-dimensional radial profiles of volumetric concentration for a velocity of the mixture of 2.6 m s−1 and for oil concentrations of 0.01 (a), 0.13 (b), and 0.22 (c). In the simulations, S1 corresponds to the Schiller–Neumann correlation and Pal (2000) equation used to calculate drag coefficient and viscosity, respectively, and S2 corresponds to the Haider–Levenspiel correlation and Pal (2000) equation to calculate drag coefficient and viscosity, respectively.

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