2021
DOI: 10.3390/pr9050880
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Hybrid Approach for Mixing Time Characterization and Scale-Up in Geometrical Nonsimilar Stirred Vessels Equipped with Eccentric Multi-Impeller Systems—An Industrial Perspective

Abstract: Multipurpose stirring and blending vessels equipped with various impeller systems are indispensable in the pharmaceutical industry because of the high flexibility necessary during multiproduct manufacturing. On the other hand, process scale-up and scale-down during process development and transfer from bench or pilot to manufacturing scale, or the design of so-called scale-down models (SDMs), is a difficult task due to the geometrical differences of used vessels. The present work comprises a hybrid approach to… Show more

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Cited by 7 publications
(5 citation statements)
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“…This can originate from multiple root causes, such as model simplification through the isotropic flow assumption by the applied RANS model, the MRF technique, frozen flow field or inequality between real and simulated measurement position. Similar errors in the range of 10% were reported in literature ( Scully et al, 2020 ), ( Martinetz et al, 2021 ) which led to the assumption that the observed deviation are in an acceptable range for the purpose of this study. On the other hand, the validity of the kinetic models to predict large-scale were investigated with a conjugation run in the GST-1, as described in chapter 2.2.6.…”
Section: Resultssupporting
confidence: 87%
See 1 more Smart Citation
“…This can originate from multiple root causes, such as model simplification through the isotropic flow assumption by the applied RANS model, the MRF technique, frozen flow field or inequality between real and simulated measurement position. Similar errors in the range of 10% were reported in literature ( Scully et al, 2020 ), ( Martinetz et al, 2021 ) which led to the assumption that the observed deviation are in an acceptable range for the purpose of this study. On the other hand, the validity of the kinetic models to predict large-scale were investigated with a conjugation run in the GST-1, as described in chapter 2.2.6.…”
Section: Resultssupporting
confidence: 87%
“…The goal is to establish an advanced process model that allows to examine the effects of scale, turbulence, and mixing parameters completely in silico . In the field of biotechnology, CFD was recently applied to study bioreactor mixing performance ( Wutz et al, 2020 ; Xing et al, 2020 ; Martinetz et al, 2021 ), predict large-scale mixing times and oxygen mass transfer ( Scully et al, 2020 ), ( Bach et al, 2017 ; Wutz et al, 2018 ; Nadal-Rey et al, 2022 ) and explore inhomogeneity effects on the cell metabolism ( Haringa et al, 2017 ). However, most studies focus on comparably slow bio-chemical processes, such as fermentation, with characteristic times in the range of min to hours, while typical chemical reactions being significantly faster (down to nano-sec).…”
Section: Introductionmentioning
confidence: 99%
“…To determine the mixing time, the widely used Θ M,95 was used, which describes the time to reach 95% homogeneity M in each cell (Eq. 20) (Kaiser et al, 2011a;Bach et al, 2017;Ebrahimi et al, 2019;Martinetz et al, 2021).…”
Section: Mixing Timementioning
confidence: 99%
“…These issues are more noticeable for the aerated mixing systems containing fluids exhibiting complex rheological behaviors. , Thus, the scale-up and design of aerated mixing systems for non-Newtonian fluids are challenging tasks. Several researchers have investigated the scale-up of aerated mixing tanks. However, there are no detailed guidelines for the scale-up of aerated mixing reactors especially for those containing complex fluids. This is due to the impacts of various parameters such as fluid type and rheology, operating conditions, and mixing system geometry on the mixing quality at different scales …”
Section: Introductionmentioning
confidence: 99%