A CFD based automatic method for compartment model development

Tannaz Tajsoleiman, Robert Spann, Christian Bach, Krist V. Gernaey, Jakob Kjøbsted Huusom, Ulrich Krühne*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Computational fluid dynamics (CFD) is a powerful tool for quantitative prediction of fluid dependent properties in a finite volume. However, the complexity of solving the momentum balances and the continuity equations at each element of the discretized geometry can easily lead to an expensive computational task. Compartment modelling is a potential alternative to speed up the calculation, which is however reached at the expense of the level of accuracy. The most important factor in optimizing a compartment model (CM) concerning the accuracy and the computational time is the quality of the chosen compartments to represent the critical gradients. This work presents a new automated compartmentalization method to characterize an improved network of compartments derived from initial detailed CFD results, with a focus on cylindrical-shaped systems. This method was evaluated with a case study of a 700 L stirred tank bioreactor by estimating the mixing performance and demonstrating its high efficiency.
Original languageEnglish
JournalComputers and Chemical Engineering
Volume123
Pages (from-to)236-245
ISSN0098-1354
DOIs
Publication statusPublished - 2019

Keywords

  • Fluid dynamics
  • CFD based compartment model
  • Automated compartmentalization
  • Mixing

Cite this

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title = "A CFD based automatic method for compartment model development",
abstract = "Computational fluid dynamics (CFD) is a powerful tool for quantitative prediction of fluid dependent properties in a finite volume. However, the complexity of solving the momentum balances and the continuity equations at each element of the discretized geometry can easily lead to an expensive computational task. Compartment modelling is a potential alternative to speed up the calculation, which is however reached at the expense of the level of accuracy. The most important factor in optimizing a compartment model (CM) concerning the accuracy and the computational time is the quality of the chosen compartments to represent the critical gradients. This work presents a new automated compartmentalization method to characterize an improved network of compartments derived from initial detailed CFD results, with a focus on cylindrical-shaped systems. This method was evaluated with a case study of a 700 L stirred tank bioreactor by estimating the mixing performance and demonstrating its high efficiency.",
keywords = "Fluid dynamics, CFD based compartment model, Automated compartmentalization, Mixing",
author = "Tannaz Tajsoleiman and Robert Spann and Christian Bach and Gernaey, {Krist V.} and Huusom, {Jakob Kj{\o}bsted} and Ulrich Kr{\"u}hne",
year = "2019",
doi = "10.1016/j.compchemeng.2018.12.015",
language = "English",
volume = "123",
pages = "236--245",
journal = "Computers & Chemical Engineering",
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publisher = "Elsevier",

}

A CFD based automatic method for compartment model development. / Tajsoleiman, Tannaz; Spann, Robert; Bach, Christian; Gernaey, Krist V.; Huusom, Jakob Kjøbsted; Krühne, Ulrich.

In: Computers and Chemical Engineering, Vol. 123, 2019, p. 236-245.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - A CFD based automatic method for compartment model development

AU - Tajsoleiman, Tannaz

AU - Spann, Robert

AU - Bach, Christian

AU - Gernaey, Krist V.

AU - Huusom, Jakob Kjøbsted

AU - Krühne, Ulrich

PY - 2019

Y1 - 2019

N2 - Computational fluid dynamics (CFD) is a powerful tool for quantitative prediction of fluid dependent properties in a finite volume. However, the complexity of solving the momentum balances and the continuity equations at each element of the discretized geometry can easily lead to an expensive computational task. Compartment modelling is a potential alternative to speed up the calculation, which is however reached at the expense of the level of accuracy. The most important factor in optimizing a compartment model (CM) concerning the accuracy and the computational time is the quality of the chosen compartments to represent the critical gradients. This work presents a new automated compartmentalization method to characterize an improved network of compartments derived from initial detailed CFD results, with a focus on cylindrical-shaped systems. This method was evaluated with a case study of a 700 L stirred tank bioreactor by estimating the mixing performance and demonstrating its high efficiency.

AB - Computational fluid dynamics (CFD) is a powerful tool for quantitative prediction of fluid dependent properties in a finite volume. However, the complexity of solving the momentum balances and the continuity equations at each element of the discretized geometry can easily lead to an expensive computational task. Compartment modelling is a potential alternative to speed up the calculation, which is however reached at the expense of the level of accuracy. The most important factor in optimizing a compartment model (CM) concerning the accuracy and the computational time is the quality of the chosen compartments to represent the critical gradients. This work presents a new automated compartmentalization method to characterize an improved network of compartments derived from initial detailed CFD results, with a focus on cylindrical-shaped systems. This method was evaluated with a case study of a 700 L stirred tank bioreactor by estimating the mixing performance and demonstrating its high efficiency.

KW - Fluid dynamics

KW - CFD based compartment model

KW - Automated compartmentalization

KW - Mixing

U2 - 10.1016/j.compchemeng.2018.12.015

DO - 10.1016/j.compchemeng.2018.12.015

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VL - 123

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JO - Computers & Chemical Engineering

JF - Computers & Chemical Engineering

SN - 0098-1354

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