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Lagrangian Modeling of Hydrodynamic-Kinetic Interactions in (Bio) Chemical Reactors: Practical Implementation and Setup Guidelines

Lagrangian Modeling of Hydrodynamic-Kinetic Interactions in (Bio) Chemical Reactors: Practical Implementation and Setup Guidelines, Cees Haringa, Henk J. Noorman, and Robert F. Mudde. Chemical Engineering Science 2017, 157 , 159–168.

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Abstract

Large substrate concentration gradients can exist in chemical or biochemical reactions, resulting from a large circulation time compared to the turnover time of substrates. The influence of such gradients on the microbial metabolism can significantly compromise optimal bioreactor performance. Lapin et ai. (2004) proposed an Euler-Lagrange CFD method to study the impact of such gradients from the microbial point of view. The discrete representation of the biomass phase yields an advantageous perspective for studying the impact of extra-cellular variations on the metabolism, but at significant computational cost. In particular, the tracked number of particles, as well as the applied time resolution, have a large impact on both the accuracy of the simulation and the runtime of the simulation. In this work we study the influence of these parameters on both the simulation results and computation time, and provide guidelines for accurate Euler-Lagrange bioreactor simulations at minimal computational cost. (C) 2016 Elsevier Ltd. All rights reserved.

BibTeX

@article{ ISI:000388828400013,
Author = {Haringa, Cees and Noorman, Henk J. and Mudde, Robert F.},
Title = {Lagrangian Modeling of Hydrodynamic-Kinetic Interactions in (Bio) Chemical Reactors: Practical Implementation and Setup Guidelines},
Journal = {Chemical Engineering Science},
Year = {2017},
Volume = {157},
Pages = {159-168},
Month = {},
Note = {},
Abstract = {Large substrate concentration gradients can exist in chemical or biochemical reactions, resulting from a large circulation time compared to the turnover time of substrates. The influence of such gradients on the microbial metabolism can significantly compromise optimal bioreactor performance. Lapin et ai. (2004) proposed an Euler-Lagrange CFD method to study the impact of such gradients from the microbial point of view. The discrete representation of the biomass phase yields an advantageous perspective for studying the impact of extra-cellular variations on the metabolism, but at significant computational cost. In particular, the tracked number of particles, as well as the applied time resolution, have a large impact on both the accuracy of the simulation and the runtime of the simulation. In this work we study the influence of these parameters on both the simulation results and computation time, and provide guidelines for accurate Euler-Lagrange bioreactor simulations at minimal computational cost. (C) 2016 Elsevier Ltd. All rights reserved.},
DOI = {10.1016/j.ces.2016.07.031},
ISSN = {0009-2509},
EISSN = {1873-4405},
Unique-ID = {ISI:000388828400013},
}

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