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TECHNICAL PAPERS

CFD Investigation of Gear Pump Mixing Using Deforming/Agglomerating Mesh

[+] Author and Article Information
Wayne Strasser

 Eastman Chemical Company, Kingsport, TN 37660strasser@eastman.com

J. Fluids Eng 129(4), 476-484 (Oct 27, 2006) (9 pages) doi:10.1115/1.2436577 History: Received December 16, 2005; Revised October 27, 2006

A moving-deforming grid study was carried out using a commercial computational fluid dynamics (CFD) solver, FLUENT ® 6.2.16. The goal was to quantify the level of mixing of a lower-viscosity additive (at a mass concentration below 10%) into a higher-viscosity process fluid for a large-scale metering gear pump configuration typical in plastics manufacturing. Second-order upwinding and bounded central differencing schemes were used to reduce numerical diffusion. A maximum solver progression rate of 0.0003 revolutions per time step was required for an accurate solution. Fluid properties, additive feed arrangement, pump scale, and pump speed were systematically studied for their effects on mixing. For each additive feed arrangement studied, the additive was fed in individual stream(s) into the pump-intake. Pump intake additive variability, in terms of coefficient of spatial variation (COV), was >300% for all cases. The model indicated that the pump discharge additive COV ranged from 45% for a single centerline additive feed stream to 5.5% for multiple additive feed streams. It was found that viscous heating and thermal/shear-thinning characteristics in the process fluid slightly improved mixing, reducing the outlet COV to 3.2% for the multiple feed-stream case. The outlet COV fell to 2.0% for a half-scale arrangement with similar physics. Lastly, it was found that if the smaller unit’s speed were halved, the outlet COV was reduced to 1.5%.

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Copyright © 2007 by American Society of Mechanical Engineers
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Figures

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Figure 1

Computational grid from a Polyflow® study (not related to present work)

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Figure 2

Typical computational grid used in present study

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Figure 3

Computational domain for the straight-through numerical diffusion test case

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Figure 11

Time-averaged outlet additive mass concentration profiles for the three full-scale cases normalized by the time-averaged MFWAA outlet concentration

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Figure 4

Normalized additive mass concentration profiles for the straight-through numerical diffusion test case

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Figure 5

Computational domain for the perimeter-flow numerical diffusion test case

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Figure 6

Typical instantaneous normalized additive mass concentration contours for a single additive injection stream and a Newtonian process fluid; white represents material having a mass concentration ⩾60% higher than the outlet instantaneous MFWAA concentration

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Figure 7

Typical instantaneous fluid vectors downstream of gear meshing zone; white represents a velocity ⩾10% higher than the gear blade tip velocity magnitude

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Figure 8

Typical instantaneous normalized additive mass concentration contours for five injection streams and a Newtonian process fluid; white represents material having a mass concentration ⩾60% higher than the instantaneous outlet MFWAA concentration

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Figure 9

Typical instantaneous normalized temperature contours for five injection streams in which VHTST effects are taken into account; white represents material having a temperature ⩾10°C higher than the inlet temperature

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Figure 10

Typical instantaneous normalized outlet process fluid viscosity, mixture temperature, and mixture strain rate magnitude for five injection streams and VHTST effects

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