Predicting the tangential velocity field in stirred tanks using the Multiple Reference Frames (MRF) model with validation by LDA measurements

Oshinowo, Lanre; Jaworski, Z.; Dyster, Kate N.; Marshall, E. M.; Nienow, Alvin W.

doi:10.1016/b978-044450476-0/50036-4

Cited by 36 publications

(29 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Because we use the MRF resolution, the reactor was divided in to non-overlapping regions, a rotating cylindrical volume that encloses the retreat impeller and an outer stationary volume that contains the remaining parts of the reactor. The interface that separates the two regions was located midway between the impeller tip and the reactor walls, which is consistent with Oshinowo et al [18]. The outer stationary volume was also divided into two parts: an irregular part near the impeller and a regular part that corresponded to the remaining volume.…”

Section: Numerical Details 21 Geometrical Details and Grid Considerasupporting

confidence: 68%

Numerical Investigation of Mixing Time in a Torus Reactor

Bekrentchir¹,

Dellal²

2016

Period. Polytech. Chem. Eng.

View full text Add to dashboard Cite

In this work, the mixing performance in a batch torus reactor was investigated using computational fluid dynamics (CFD) IntroductionTorus reactor has emerged as one of the most promising devices in chemical, biochemical and environmental engineering operations. It is particularly well-suited for processes that demand rapid and uniform distribution of the reaction components, e.g., polymerization [1], and multiphase systems that require high mass and heat transfer, e.g., enzymatic and photobiological reactions [2][3][4]. The combination of the swirl flow generated by the impeller rotation with Dean vortices that appear when an axial flow occurs in the bends efficiently mixes the reactants, produces intense dispersing effects and leads to an absence of dead volumes in the reactor [5,6]. Furthermore, the loop configuration involves a low-pressure drop, which reduces power consumption for a given mixing operation [7].Sato et al. [8] were the first to study the flow pattern in the torus reactor. They developed an empirical correlation based on a simple discharge flow model to predict the mean bulk velocity as a function of the type of the impeller, blade angle, impeller diameter, impeller speed and baffle. This model indicates that the resulting flow is mainly a function of the impeller speed and the sine of the impeller blade angle. Murakami et al. [9] predicted the effect of the reactor geometry, baffles, impeller type, blade angle, impeller diameter, impeller speed and operating mode on the power consumption. They found that the power number is proportional to (sin φ) 2 in the region of high mixing Reynolds number (Re > 10 4 ); where φ is the impeller blade angle and almost independent of the baffles and operation mode. Tanaka et al. [10] used the ratio of the circulation Reynolds number to the mixing Reynolds number to explore the effect of the reactor diameter, impeller diameter, impeller speed and fluid properties on the mean bulk velocity. They also developed a new correlation relate the power consumption in the torus reactor to the impeller speed and geometrical characteristics of the reactor and the impeller. Other researchers investigated the hydrodynamic characteristics of the torus reactor using residence time distribution (RTD) technique. Belleville et al. [11] employed the axial dispersed plug flow with complete circulation to model the batch torus reactor and proposed a new correlation for the dimensionless mixing

show abstract

Section: Numerical Details 21 Geometrical Details and Grid Considerasupporting

confidence: 68%

Numerical Investigation of Mixing Time in a Torus Reactor

Bekrentchir¹,

Dellal²

2016

Period. Polytech. Chem. Eng.

View full text Add to dashboard Cite

show abstract

“…One technique to achieve this is based on sliding meshes [9]. A much simpler approach is the so-called multiple reference frame (MRF) technique [10]. The computational domain is divided again into two zones similar to the older experimental data based technique.…”

Section: Single Phase Hydrodynamicsmentioning

confidence: 99%

A CFD-based simulation study of a large scale flocculation tank for potable water treatment

Samaras

Zouboulis

Karapantsios

et al. 2010

Chemical Engineering Journal

View full text Add to dashboard Cite

“…Their study concluded that the results predicted by the ASM compare better with the experimental data than those predicted by the standard k-model. Oshinowo et al (2000) performed the CFD study using different turbulence models like, k-, RNG kand RSM for the prediction of tangential velocity distribution in a baffled vessel using multiple reference frame (MRF) model. The tangential velocity distribution above the impeller has been correctly predicted.…”

Section: Reynolds Stress Modelingmentioning

confidence: 99%