Velocity profiles in a closed, unbaffled vessel: Comparison between experimental LDV data and numerical CFD predictions

Document Type

Article

Publication Date

10-1-1997

Abstract

The velocity profiles and the turbulent kinetic energy distribution were obtained for the flow generated by a 6-blade, 45°pitched-blade turbine in an unbaffled, flat-bottom, cylindrical tank provided with a lid, and completely filled with water. The mean and fluctuating velocities in all three directions were experimentally measured with a laser-Doppler velocimeter (LDV) at five different heights and twenty radial positions within the vessel. A computational fluid dynamic (CFD) software package (FLUENT) was used to numerically predict the velocity distribution, fluctuating velocities, power consumption, and pumping capacity of the impeller. Turbulence effects were simulated using either the k-ε model or the algebraic stress model (ASM). The experimentally obtained mean velocities and turbulent kinetic energies on the top and bottom horizontal surfaces of the region swept by the impeller were used as boundary conditions in the simulations. The agreement between the experimental data and the numerical predictions was found to be significant in most cases. Velocity predictions based on ASM were found to be superior to those based on the k-ε model. In general the tangential velocities were found to be significantly bigger than the other two velocity components. In the r-Z plane a strong radially oriented flow was observed to emerge from the impeller, producing two main recirculation flows, one above and the other below the impeller. The dimensionless mean velocities in all three components and the dimensionless turbulent kinetic energies were found to be nearly independent of the impeller rotational speed.

Identifier

0031255711 (Scopus)

Publication Title

Chemical Engineering Science

External Full Text Location

https://doi.org/10.1016/S0009-2509(97)00150-4

ISSN

00092509

First Page

3483

Last Page

3492

Issue

20

Volume

52

Grant

EEC 9520573

Fund Ref

National Science Foundation

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