On the derivation of graphically inspired feasibility constraints for distillation network synthesis

Joonjae Ryu; Christos T. Maravelias

doi:10.1002/aic.17740

On the derivation of graphically inspired feasibility constraints for distillation network synthesis

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

Abstract

We propose the integration of simplified graphically inspired feasibility constraints into optimization-based models for distillation network synthesis. The approach facilitates the use of surrogate, potentially data-based, distillation column models while considering feasibility in a computationally efficient manner. The proposed approach can aid the formulation of efficient approaches for preliminary distillation network synthesis.

Original language	English (US)
Article number	e17740
Journal	AIChE Journal
Volume	68
Issue number	7
DOIs	https://doi.org/10.1002/aic.17740
State	Published - Jul 2022
Externally published	Yes

All Science Journal Classification (ASJC) codes

Biotechnology
Environmental Engineering
General Chemical Engineering

Keywords

optimization
process synthesis
superstructure-based process synthesis

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10.1002/aic.17740

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title = "On the derivation of graphically inspired feasibility constraints for distillation network synthesis",

abstract = "We propose the integration of simplified graphically inspired feasibility constraints into optimization-based models for distillation network synthesis. The approach facilitates the use of surrogate, potentially data-based, distillation column models while considering feasibility in a computationally efficient manner. The proposed approach can aid the formulation of efficient approaches for preliminary distillation network synthesis.",

keywords = "optimization, process synthesis, superstructure-based process synthesis",

author = "Joonjae Ryu and Maravelias, \{Christos T.\}",

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year = "2022",

month = jul,

doi = "10.1002/aic.17740",

language = "English (US)",

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AU - Ryu, Joonjae

AU - Maravelias, Christos T.

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N2 - We propose the integration of simplified graphically inspired feasibility constraints into optimization-based models for distillation network synthesis. The approach facilitates the use of surrogate, potentially data-based, distillation column models while considering feasibility in a computationally efficient manner. The proposed approach can aid the formulation of efficient approaches for preliminary distillation network synthesis.

AB - We propose the integration of simplified graphically inspired feasibility constraints into optimization-based models for distillation network synthesis. The approach facilitates the use of surrogate, potentially data-based, distillation column models while considering feasibility in a computationally efficient manner. The proposed approach can aid the formulation of efficient approaches for preliminary distillation network synthesis.

KW - optimization

KW - process synthesis

KW - superstructure-based process synthesis

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U2 - 10.1002/aic.17740

DO - 10.1002/aic.17740

M3 - Letter

AN - SCOPUS:85131710401

SN - 0001-1541

VL - 68

JO - AIChE Journal

JF - AIChE Journal

IS - 7

M1 - e17740

ER -

On the derivation of graphically inspired feasibility constraints for distillation network synthesis

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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