Numerical Simulation of the Influence of Bottom Structures on the Flow Field Characteristic in Shaking Bioreactors

Lu, Zhiming; Li, Chengtuo; Huang, Liuyi; Zhong, Fengping; Fei, Liangqi; Zhang, Hongliang; Pan, Yong

doi:10.1252/jcej.20we022

Cited by 1 publication

(1 citation statement)

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“…Although the suspension ability was greatly enhanced, the energy consumption, however, was 10-100 times higher compared with that of the traditional shaking tank (Isobe et al, 2020). Lu et al (2020) has considered the impact of a geometrical change by equipping the shaking bioreactor with a conical bottom. In their study, it was demonstrated that the conical bottom is superior to bottoms with other shapes, such as ellipsoid, at, and spherical bottoms, because of its bene cial characteristics, such as lower shear damage and high-e ciency oxygen mixing.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Optimization for Hydrodynamic Characterization of a Cylindrical Orbitally Shaken Bioreactor with a Bump at the Bottom

Wang

Isobe

Okano

et al. 2021

J. Chem. Eng. Japan

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An orbitally shaken bioreactor is the most popular system for cell cultivation in a suspension culture owing to its unique characteristics. However, conventional bioreactors struggle to meet the anticipated demand in practical applications due to their limitations. In this study, numerical simulations are conducted to evaluate the performance of a newly developed orbitally shaken bioreactor that is equipped with a vaulted "bump" at the bottom wall. The presence of this bump signi cantly improves the mass transfer and cell suspension ratio in the culture medium without increasing the shear stress; it also e ciently reduces the cell aggregation in the central part at the bottom wall. In addition, to enable a suitable cell culture environment for practical applications, the Bayesian algorithm is employed to optimize the control of three parameters, namely bump height (h b ), shaking velocity (ω), and shaking radius (R), of this reactor. For all the cases considered, the obtained data related to mass transfer, suspension ratio, and shear stress are analyzed. The simulation results show that the optimal bioreactor is preferable for cell cultivation compared with the initial state, owing to its high capability for mass transfer and suspending cells. It can be concluded that the methodology described in this paper is a feasible and reliable tool for performance prediction and process optimization in biotechnology.

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Section: Introductionmentioning

confidence: 99%