CFD-based genetic programming model for liquid entry pressure estimation of hydrophobic membranes

Hooman Chamani; Pelin Yazgan-Birgi; Takeshi Matsuura; Dipak Rana; Mohamed I. Hassan Ali; Hassan A. Arafat; Christopher Q. Lan

doi:10.1016/j.desal.2019.114231

CFD-based genetic programming model for liquid entry pressure estimation of hydrophobic membranes

Hooman Chamani, Pelin Yazgan-Birgi, Takeshi Matsuura, Dipak Rana, Mohamed I. Hassan Ali, Hassan A. Arafat, Christopher Q. Lan

University of Ottawa

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

Abstract

Wetting phenomenon inside the pore is a significant obstacle hindering membrane distillation (MD) from being fully industrialized. Herein, a new equation is provided for the users, using the combination of computational fluid dynamics (CFD) and genetic programming (GP) tools for estimation of liquid entry pressure (LEP), a parameter closely related to pore wetting. CFD was applied to model the wetting process inside the pore during the gradual increase in feed pressure at different scenarios in which contact angle, pore radius and membrane thickness were changed. Afterwards, GP as an intelligent method was employed to provide a computer program estimating LEP in the whole ranges in which CFD modeling was carried out. Moreover, validation was done using experimental data and then the influence of effective parameters on LEP was studied. This work provides an explicit formula for estimation of LEP in a closer agreement with the experimental data in comparison to the Young-Laplace equation. In addition, the influence of the membrane thickness was added to the equation, providing a more realistic formula for LEP estimation.

Original language	British English
Article number	114231
Journal	Desalination
Volume	476
DOIs	https://doi.org/10.1016/j.desal.2019.114231
State	Published - 15 Feb 2020

Keywords

Computational fluid dynamics
Genetic programming
Liquid entry pressure
Membrane distillation
Modeling

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title = "CFD-based genetic programming model for liquid entry pressure estimation of hydrophobic membranes",

abstract = "Wetting phenomenon inside the pore is a significant obstacle hindering membrane distillation (MD) from being fully industrialized. Herein, a new equation is provided for the users, using the combination of computational fluid dynamics (CFD) and genetic programming (GP) tools for estimation of liquid entry pressure (LEP), a parameter closely related to pore wetting. CFD was applied to model the wetting process inside the pore during the gradual increase in feed pressure at different scenarios in which contact angle, pore radius and membrane thickness were changed. Afterwards, GP as an intelligent method was employed to provide a computer program estimating LEP in the whole ranges in which CFD modeling was carried out. Moreover, validation was done using experimental data and then the influence of effective parameters on LEP was studied. This work provides an explicit formula for estimation of LEP in a closer agreement with the experimental data in comparison to the Young-Laplace equation. In addition, the influence of the membrane thickness was added to the equation, providing a more realistic formula for LEP estimation.",

keywords = "Computational fluid dynamics, Genetic programming, Liquid entry pressure, Membrane distillation, Modeling",

author = "Hooman Chamani and Pelin Yazgan-Birgi and Takeshi Matsuura and Dipak Rana and {Hassan Ali}, {Mohamed I.} and Arafat, {Hassan A.} and Lan, {Christopher Q.}",

note = "Funding Information: The authors greatly acknowledge the support of Natural Sciences and Engineering Research Council of Canada ( NSERC ) individual discovery grant RGPIN-2014-03753 . The work at Khalifa University was supported through the Center for Membrane and Advanced Water Technology (CMAT), under Award No. RC2-2018-009 . Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",

year = "2020",

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doi = "10.1016/j.desal.2019.114231",

language = "British English",

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journal = "Desalination",

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T1 - CFD-based genetic programming model for liquid entry pressure estimation of hydrophobic membranes

AU - Chamani, Hooman

AU - Yazgan-Birgi, Pelin

AU - Matsuura, Takeshi

AU - Rana, Dipak

AU - Hassan Ali, Mohamed I.

AU - Arafat, Hassan A.

AU - Lan, Christopher Q.

N1 - Funding Information: The authors greatly acknowledge the support of Natural Sciences and Engineering Research Council of Canada ( NSERC ) individual discovery grant RGPIN-2014-03753 . The work at Khalifa University was supported through the Center for Membrane and Advanced Water Technology (CMAT), under Award No. RC2-2018-009 . Publisher Copyright: © 2019 Elsevier B.V.

PY - 2020/2/15

Y1 - 2020/2/15

N2 - Wetting phenomenon inside the pore is a significant obstacle hindering membrane distillation (MD) from being fully industrialized. Herein, a new equation is provided for the users, using the combination of computational fluid dynamics (CFD) and genetic programming (GP) tools for estimation of liquid entry pressure (LEP), a parameter closely related to pore wetting. CFD was applied to model the wetting process inside the pore during the gradual increase in feed pressure at different scenarios in which contact angle, pore radius and membrane thickness were changed. Afterwards, GP as an intelligent method was employed to provide a computer program estimating LEP in the whole ranges in which CFD modeling was carried out. Moreover, validation was done using experimental data and then the influence of effective parameters on LEP was studied. This work provides an explicit formula for estimation of LEP in a closer agreement with the experimental data in comparison to the Young-Laplace equation. In addition, the influence of the membrane thickness was added to the equation, providing a more realistic formula for LEP estimation.

AB - Wetting phenomenon inside the pore is a significant obstacle hindering membrane distillation (MD) from being fully industrialized. Herein, a new equation is provided for the users, using the combination of computational fluid dynamics (CFD) and genetic programming (GP) tools for estimation of liquid entry pressure (LEP), a parameter closely related to pore wetting. CFD was applied to model the wetting process inside the pore during the gradual increase in feed pressure at different scenarios in which contact angle, pore radius and membrane thickness were changed. Afterwards, GP as an intelligent method was employed to provide a computer program estimating LEP in the whole ranges in which CFD modeling was carried out. Moreover, validation was done using experimental data and then the influence of effective parameters on LEP was studied. This work provides an explicit formula for estimation of LEP in a closer agreement with the experimental data in comparison to the Young-Laplace equation. In addition, the influence of the membrane thickness was added to the equation, providing a more realistic formula for LEP estimation.

KW - Computational fluid dynamics

KW - Genetic programming

KW - Liquid entry pressure

KW - Membrane distillation

KW - Modeling

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CFD-based genetic programming model for liquid entry pressure estimation of hydrophobic membranes

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