CFD Simulation and Experimental Validation of Fluid Flow in Liquid Distributors

Heggemann, M.; Hirschberg, Stefan; Spiegel, Lothar; Bachmann, C.

doi:10.1205/cherd06093

Cited by 21 publications

(12 citation statements)

References 2 publications

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“…The closure problem is discussed for each model and the three models are compared according to several criteria. Heggemann et al 15 modeled the fluid flow in liquid distributors and the validation was accomplished in the uniform distribution of liquid above structured packings for its performance prediction.…”

Section: Introductionmentioning

confidence: 99%

Volume‐of‐fluid‐based model for multiphase flow in high‐pressure trickle‐bed reactor: Optimization of numerical parameters

Lopes

Quinta‐Ferreira

2009

AIChE Journal

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Aiming to understand the effect of various parameters such as liquid velocity, surface tension, and wetting phenomena, a Volume-of-Fluid (VOF) model was developed to simulate the multiphase flow in high-pressure trickle-bed reactor (TBR). As the accuracy of the simulation is largely dependent on mesh density, different mesh sizes were compared for the hydrodynamic validation of the multiphase flow model. Several model solution parameters comprising different time steps, convergence criteria and discretization schemes were examined to establish model parametric independency results. High-order differencing schemes were found to agree better with the experimental data from the literature given that its formulation includes inherently the minimization of artificial numerical dissipation. The optimum values for the numerical solution parameters were then used to evaluate the hydrodynamic predictions at highpressure demonstrating the significant influence of the gas flow rate mainly on liquid holdup rather than on two-phase pressure drop and exhibiting hysteresis in both hydrodynamic parameters. Afterwards, the VOF model was applied to evaluate successive radial planes of liquid volume fraction at different packed bed cross-sections.

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Section: Introductionmentioning

confidence: 99%

Volume‐of‐fluid‐based model for multiphase flow in high‐pressure trickle‐bed reactor: Optimization of numerical parameters

Lopes

Quinta‐Ferreira

2009

AIChE Journal

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“…Lateral velocity prevents liquid from turning at the edge of an orifice, resulting in flow separation at the orifice. Heggeman et al found that orifice flow in a liquid distributor was influenced by lateral velocity [8]. Through a series of pipe section simulation experiments, Jia studied leakage under different pipe diameters, pressures and leakage areas.…”

Section: Introductionmentioning

confidence: 99%

Experimental and numerical modeling of sidewall orifices

Cheng

Shen

2020

SN Appl. Sci.

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The discharge coefficient of an orifice is important for the outflow through the orifice. While it cannot be quantified theoretically as the outflow through an orifice depends on a number of parameters such as the pipe pressure, the liquid velocity and the shape and the area of the orifice. In this study, experiments and computational fluid dynamics (CFD) simulations were performed to find out the factors influencing discharge coefficient and the corresponding mechanism. The CFD simulation is based on Navier-Stokes equations combined with RNG k − ε turbulence model. The results show that a negative exponential function could fit the relationship between orifice discharge coefficient, pipe pressure, and orifice area more accurately. The relationship between the discharge coefficient of the orifice and the velocity was linear. In general, the simulation results fit well with the experimental results, which indicates that CFD simulation could be used to study pipeline leakage.Keywords Outflow · Orifice · Velocity · Pressure · Numerical model · Computational fluid dynamics (CFD) Abbreviations Q totalThe inlet flow rate, m 3 /s Q outThe outflow rate, m 3 /s Q endThe outlet flow rate, m 3 /s A crossThe area of the cross-section, m 2 k aThe ration of the orifice area which represents the relative size of the orifice area H 1The upstream water head, m P a Atmospheric pressure, P a ρThe water density, kg/m 3 gThe gravity constant, 9.8 m/s 2 α 0The kinetic energy correction factor of the inlet flow ν comeThe upstream velocity, m/s P outThe pressure of the shrinkage section out of the orifice, P a α outThe kinetic energy correction factor of the orifice outflow h w

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“…The model solves the standard three-dimensional Reynoldsaveraged Navier-Stokes and continuity equations for steady state turbulent flow based on the k-ω SST turbulence model [26]. Some previous studies [11,16] use the standard k-ε turbulence model; however, the boundary layer is greatly resolved in the present study, and the k-ω SST turbulence model is more feasible in our case [26]. The pressure based solver is applied, and the working fluid is incompressible air.…”

Section: Cfd Modelmentioning

confidence: 99%

“…There are four approaches to investigate flow distribution and pressure drop in a flow manifold: analytical models [4][5][6][7], computational fluid dynamics (CFD) models [9][10][11][12][13][14][15][16], discrete models [17][18][19] and experimental measurements [11,14,[20][21][22].…”

Section: Introductionmentioning

confidence: 99%