Novel evaluation method to determine the local mixing time distribution in stirred tank reactors

Fitschen, Jürgen; Hofmann, Sebastian; Wutz, Johannes; Kameke, Alexandra von; Hoffmann, Marko; Wucherpfennig, Thomas; Schlüter, Michael

doi:10.1016/j.cesx.2021.100098

Cited by 27 publications

(52 citation statements)

References 41 publications

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“…Mixing is crucial to many process scale-up projects. [1][2][3][4] It affects a diverse range of chemically-intensive processes such as phase-transfer catalysis, [5][6][7][8] additive manufacturing, [9][10][11] fuel combustion, 12 flow chemistry, 13 powder formulation, 14,15 biotechnology, 16 and (most pertinent to this paper) myriad reaction scale-ups in tank reactors. [16][17][18][19][20] Mixing represents one of the most effective, non-chemical means of process improvement.…”

Section: Impact Of Mixingmentioning

confidence: 99%

“…From the aforementioned imaging innovations in mixing analysis, 2,14,15,[24][25][26][27][28]30,[35][36][37][38][39]41,42,[45][46][47][47][48][49][50][51][52][53] most of these are disparately reported, differently encoded, and not comparable within a single platform. Herein, we employ a series of mixing case studies to compare analysis derived from the core Kineticolor platform, tracking an averaged color region over time, as well as newly-integrated and spatially-resolved mixing metrics.…”

Section: Aimsmentioning

confidence: 99%

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Computer Vision for Kinetic Analysis of Lab- and Process-scale Mixing Phenomena

Barrington,

Dickinson,

McGuire

et al. 2022

Preprint

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A software platform for the computer vision-enabled analysis of mixing phenomena of relevance to process scale-up is described. By bringing new and known time-resolved mixing metrics under one platform, hitherto unavailable comparisons of pixel-derived mixing metrics are exemplified across non-chemical and chemical processes. The analytical methods described are applicable using any camera and across an appreciable range of reactor scales, from development through to process scale-up. A case study in nucleophilic aromatic substitution run on 5L-scale shows how camera and offline concentration measurements can be correlated. In some cases, it can be shown that camera data holds the power to predict reaction progress.

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Section: Impact Of Mixingmentioning

confidence: 99%

Section: Aimsmentioning

confidence: 99%

Computer Vision for Kinetic Analysis of Lab- and Process-scale Mixing Phenomena

Barrington,

Dickinson,

McGuire

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…To the best of our knowledge, few works on the mixing process (viz. Essi [2], Ploypetchara et al [3], Kim et al [5], Jasikova et al [9], and Fitschen et al [12], among others) are available in the literature. However, very few researchers ( [84,85]) considered the combination of the mixing process as well as manufacturing process in his/her work.…”

Section: Research Gap and Contributionsmentioning

confidence: 99%

“…Thus, in the area of inventory control, investigation of the production inventory problem of a mixed product along with the mixing process is an intersecting research area. In this connection, Nienow et al [10], Cheng et al [11], Fitschen et al [12], and many others have had a valuable influence in this area. As various inventory parameters like production rate, demand rate, deterioration rate, and preservation technology play a significant role to control a production inventory, researchers should take more care of those inventory parameters in the studying of the production inventory problem with the mixing process.…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model of the Production Inventory Problem for Mixing Liquid Considering Preservation Facility

et al. 2021

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The mixing process of liquid products is a crucial activity in the industry of essential commodities like, medicine, pesticide, detergent, and so on. So, the mathematical study of the mixing problem is very much important to formulate a production inventory model of such type of items. In this work, the concept of the mixing problem is studied in the branch of production inventory. Here, a production model of mixed liquids with price-dependent demand and a stock-dependent production rate is formulated under preservation technology. In the formulation, first of all, the mixing process is presented mathematically with the help of simultaneous differential equations. Then, the mixed liquid produced in the mixing process is taken as a raw material of a manufacturing system. Then, all the cost components and average profit of the system are calculated. Now, the objective is to maximize the corresponding profit maximization problem along with the highly nonlinear objective function. Because of this, the mentioned maximization problem is solved numerically using MATHEMATICA software. In order to justify the validity of the model, two numerical examples are worked out. Finally, to show the impact of inventory parameters on the optimal policy, sensitivity analyses are performed and the obtained results are presented graphically.

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“…Prediction quality of obtained steady flow fields and power numbers are shown by Particle Image Velocimetry (PIV) or laser-doppler anemometry (LDA) and torque measurements [11,12,19,28]. LB methods have just recently become popular in the biopharmaceutical industry due to the availability of new commercial solvers [27,29,30]. Only a few articles have been published on LB LES for stirred tanks, lacking information on the quality of flow field prediction.…”

Section: Introductionmentioning

confidence: 99%

Validation of Novel Lattice Boltzmann Large Eddy Simulations (LB LES) for Equipment Characterization in Biopharma

et al. 2021

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Detailed process and equipment knowledge is crucial for the successful production of biopharmaceuticals. An essential part is the characterization of equipment for which Computational Fluid Dynamics (CFD) is an important tool. While the steady, Reynolds-averaged Navier–Stokes (RANS) k − ε approach has been extensively reviewed in the literature and may be used for fast equipment characterization in terms of power number determination, transient schemes have to be further investigated and validated to gain more detailed insights into flow patterns because they are the method of choice for mixing time simulations. Due to the availability of commercial solvers, such as M-Star CFD, Lattice Boltzmann simulations have recently become popular in the industry, as they are easy to set up and require relatively low computing power. However, extensive validation studies for transient Lattice Boltzmann Large Eddy Simulations (LB LES) are still missing. In this study, transient LB LES were applied to simulate a 3 L bioreactor system. The results were compared to novel 4D particle tracking (4D PTV) experiments, which resolve the motion of thousands of passive tracer particles on their journey through the bioreactor. Steady simulations for the determination of the power number followed a structured workflow, including grid studies and rotating reference frame volume studies, resulting in high prediction accuracy with less than 11% deviation, compared to experimental data. Likewise, deviations for the transient simulations were less than 10% after computational demand was reduced as a result of prior grid studies. The time averaged flow fields from LB LES were in good accordance with the novel 4D PTV data. Moreover, 4D PTV data enabled the validation of transient flow structures by analyzing Lagrangian particle trajectories. This enables a more detailed determination of mixing times and mass transfer as well as local exposure times of local velocity and shear stress peaks. For the purpose of standardization of common industry CFD models, steady RANS simulations for the 3 L vessel were included in this study as well.

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Novel evaluation method to determine the local mixing time distribution in stirred tank reactors

Cited by 27 publications

References 41 publications

Computer Vision for Kinetic Analysis of Lab- and Process-scale Mixing Phenomena

Computer Vision for Kinetic Analysis of Lab- and Process-scale Mixing Phenomena

A Mathematical Model of the Production Inventory Problem for Mixing Liquid Considering Preservation Facility

Validation of Novel Lattice Boltzmann Large Eddy Simulations (LB LES) for Equipment Characterization in Biopharma

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