Zum überflutungsverhalten zwei‐ und dreiphasig betriebener Rührreaktoren

Wiedmann, Josef Anselm

doi:10.1002/cite.330550904

Cited by 11 publications

(1 citation statement)

References 14 publications

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“…Several researchers have proposed a correlation between Fr and Fl to distinguish loading and well-dispersed regime; three examples; see Eqs. ( 5), ( 6) and ( 7) (Dickery et al 1983 [32], Zlokarnik et al 1967 [33], Rosseburg et al 2018 [19]):…”

Section: Operating Parametersmentioning

confidence: 99%

Dynamic generation of aqueous foams and fiber foams in a mixing tank

et al. 2021

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Mixing tanks are employed in paper and pulp industries to generate aqueous foams and fiber foams. The aim of the present study was to investigate the effect of impeller geometry on dynamic foam generation in a 60 L mixing tank. Three impeller geometries including two radial—Rushton turbine (RT), Bakker turbine (BT6), one axial high solidity pitched blade turbine (HSPBT), and four dual impeller combinations were investigated. Compressed air, water and sodium dodecyl sulphate were used as gas phase, liquid phase and surfactant, respectively, to generate aqueous foam. 1% mass consistency softwood fiber was used to generate fiber foam. The change in aqueous foam density for any given impeller was limited to ± 40 kg/m3 indicating foam density was dictated by impeller type rather than power input. Single impellers generated bubbly liquids whereas dual impellers generated low-density aqueous foams. Besides, stable foam was produced even at low power input compared to single impellers due to increase in impeller swept volume and blade contact area. Addition of fibers increased the foam density by ~ 100–150 kg/m3 and reduced the half-life time by almost threefold for all impellers due to lower air content and higher bubble size. Placement of high shear impeller (BT6) at bottom and down-pumping axial impeller (HSPBT) on top generated fine bubbles.

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Section: Operating Parametersmentioning

confidence: 99%

Dynamic generation of aqueous foams and fiber foams in a mixing tank

et al. 2021

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Literature

2001

Stirring

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Simulated oxygen and glucose gradients as a prerequisite for predicting industrial scale performance a priori

Kuschel

2020

Biotech & Bioengineering

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Transferring bioprocesses from lab to industrial scale without loss of performance is key for the successful implementation of novel production approaches. Because mixing and mass transfer is usually hampered in large scale, cells experience heterogeneities eventually causing deteriorated yields, that is, reduced titers, productivities, and sugar‐to‐product conversions. Accordingly, reliable and easy‐to‐implement tools for a priori prediction of large‐scale performance based on dry and wet‐lab tests are heavily needed. This study makes use of computational fluid dynamic simulations of a multiphase multi‐impeller stirred tank in pilot scale. So‐called lifelines, records of 120,000 Corynebacterium glutamicum cells experiencing fluctuating environmental conditions, were identified and used to properly design wet‐lab scale‐down (SD) devices. Physical parameters such as power input, gas hold up, , and mixing time showed good agreement with experimental measurements. Analyzing the late fed‐batch cultivation revealed that the complex double gradient of glucose and oxygen can be translated into a wet‐lab SD setup with only few compartments. Most remarkably, the comparison of different mesh sizes outlined that even the coarsest approach with a mesh density of was sufficient to properly predict physical and biological readouts. Accordingly, the approach offers the potential for the thorough analysis of realistic industrial case scenarios.

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Zum überflutungsverhalten zwei‐ und dreiphasig betriebener Rührreaktoren

Cited by 11 publications

References 14 publications

Dynamic generation of aqueous foams and fiber foams in a mixing tank

Dynamic generation of aqueous foams and fiber foams in a mixing tank

Literature

Simulated oxygen and glucose gradients as a prerequisite for predicting industrial scale performance a priori

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