Enhanced in situ dynamic method for measuring KLa in fermentation media

Patel, Nilesh; Thibault, Jules

doi:10.1016/j.bej.2009.07.001

Cited by 13 publications

(2 citation statements)

References 16 publications

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“…This understanding can only be achieved if the hydrodynamic and physical mechanisms which are responsible for these gradients are understood in detail through experimental and numerical tools. There are various methods for measuring k L in general [8,20,21] allowing mass transfer to be measured as a complex phenomenon; however, the measurement of individual components, namely the interfacial area a, is of particular interest, since it allows determination of the factors that specifically affect the interfacial surface known as the most important component of the mass transfer process when aiming to achieve high efficiency of technological processes based on the mass transfer.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Mass Transfer Coefficient in Jet Bioreactors with Classical Computer Vision Methods and Neural Networks Algorithms

et al. 2023

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Development of energy-efficient and high-performance bioreactors requires progress in methods for assessing the key parameters of the biosynthesis process. With a wide variety of approaches and methods for determining the phase contact area in gas–liquid flows, the question of obtaining its accurate quantitative estimation remains open. Particularly challenging are the issues of getting information about the mass transfer coefficients instantly, as well as the development of predictive capabilities for the implementation of effective flow control in continuous fermentation both on the laboratory and industrial scales. Motivated by the opportunity to explore the possibility of applying classical and non-classical computer vision methods to the results of high-precision video records of bubble flows obtained during the experiment in the bioreactor vessel, we obtained a number of results presented in the paper. Characteristics of the bioreactor’s bubble flow were estimated first by classical computer vision (CCV) methods including an elliptic regression approach for single bubble boundaries selection and clustering, image transformation through a set of filters and developing an algorithm for separation of the overlapping bubbles. The application of the developed method for the entire video filming makes it possible to obtain parameter distributions and set dropout thresholds in order to obtain better estimates due to averaging. The developed CCV methodology was also tested and verified on a collected and labeled manual dataset. An onwards deep neural network (NN) approach was also applied, for instance the segmentation task, and has demonstrated certain advantages in terms of high segmentation resolution, while the classical one tends to be more speedy. Thus, in the current manuscript both advantages and disadvantages of the classical computer vision method (CCV) and neural network approach (NN) are discussed based on evaluation of bubbles’ number and their area defined. An approach to mass transfer coefficient estimation methodology in virtue of obtained results is also represented.

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Section: Introductionmentioning

confidence: 99%

Assessing the Mass Transfer Coefficient in Jet Bioreactors with Classical Computer Vision Methods and Neural Networks Algorithms

et al. 2023

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“…To date the significant scientific knowledge is accumulated and expressed in a number of classical and recent works [6][7][8][9][10][11][12][13][14][15][16], in particular, reviews [9,15], describing studies on the change (evolution) of the structural parameters of gas-liquid media under various conditions. Meanwhile besides the pure fundamental demand to clarify the interrelations between the particles in the system, for applied problems related to the calculation of mass transfer [5,17,18], it is especially important to determine the value of the interfacial surface and the local mass transfer coefficient since the crucial technological characteristic, namely the volumetric liquid-phase mass transfer coefficient k L a, might be calculated [4,12,[19][20][21], representing in essence a key performance indicator of mass transfer apparatus, bioreactors [22,23]. Another meaningful characteristic of the system to be mentioned is gas (oxygen in our case) transfer rate being inversely proportional to the liquid volume.…”

Section: Introductionmentioning

confidence: 99%

Influence of the gas–liquid non-equilibrium media structure on the mass transfer dynamics in biophysical processes

Nizovtseva,

Starodumov,

Lezhnin

et al. 2023

Smart Mater. Struct.

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Multiphase biophysical media are known to be complex structures with continuous high demand to the scientific community for understanding the relationships and ratios between factors affecting the type, dynamics and nature of its structural changes on their impact degree on the media itself. Among the plentiful list of such factors the following do worth mentioning: the lifetime of a particle, turbulence factors and a number of others, each requiring careful analysis, assessment of the contribution degree and, importantly, correct accounting. The present study is focused on such a factor affecting mass transfer intensity change as surface tension through its relationship with the interfacial area: the latter is the site of mass exchange between the gas and liquid phases, and modifications in surface tension values can significantly impact the characteristics of this area, hence altering the rate of mass transfer. By controlling surface tension, one can effectively modulate the size and stability of particles, namely bubbles or droplets, which in turn changes the interfacial area available for mass transfer. The total interfacial area, which is the cumulative surface area of all bubbles, serves as the site for mass transfer. The impact of the surface tension coefficient variation into gas–liquid mass transfer characteristics is analyzed both for the case of water and model liquid. The latter means the potential contribution of surface-active substances was a part of research scope since it was applied to recreate conditions similar to the cultural liquid when microorganisms that produce surfactants are grown. The proposed new methodology assumes calculating interfacial area through the segmentation of images captured by a high-speed camera, thus we can gain a profoundly enhanced understanding of the relationship between surface tension and mass transfer. The precise visual data and subsequent computation of the interfacial area provide deeper insights into the dynamics of bubble formation and the effects of surface tension on bubble size and distribution. As a result, this method has significantly improved our capacity to investigate and optimize mass transfer processes in multiphase biophysical systems. Both analytical approach and results interpretation not only influence affirmatively on deep understanding of natural mechanisms in biophysical media, but also might serve their best for potential application, e.g. in the context of the development of biotechnological industries based on fermentation processes for protein production.

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Effect of aeration and agitation on yeast inulinase production: a biocalorimetric investigation

Santharam

Easwaran

Mohanakrishnan

et al. 2019

Bioprocess Biosyst Eng

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Enhanced in situ dynamic method for measuring KLa in fermentation media

Cited by 13 publications

References 16 publications

Assessing the Mass Transfer Coefficient in Jet Bioreactors with Classical Computer Vision Methods and Neural Networks Algorithms

Assessing the Mass Transfer Coefficient in Jet Bioreactors with Classical Computer Vision Methods and Neural Networks Algorithms

Influence of the gas–liquid non-equilibrium media structure on the mass transfer dynamics in biophysical processes

Effect of aeration and agitation on yeast inulinase production: a biocalorimetric investigation

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