Efficient integration of optimal solvent and process design using molecular clustering

Athanasios I. Papadopoulos, Patrick Linke

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

We present a molecular clustering approach for the efficient incorporation of solvent design information into process synthesis in the integrated design of solvent/process systems. The approach is to be used in conjunction with an integrated solvent/process design approach where the solvent design stage utilises multi-objective optimisation in order to identify Pareto optimal solvent candidates that are subsequently evaluated in a process synthesis stage. We propose to introduce the solvent design information into the process synthesis stage through the use of molecular clusters. The partitioning of the original Pareto optimal set of solvents leads to smaller compact groups of similar solvent molecules from which representative molecules are introduced into the process synthesis model as discrete options to determine the optimal process performance associated with the optimal solvent. We investigate two clustering strategies, serial and parallel clustering, that allow to effectively exploit the solvent-process design interactions to minimise the computational demands of the process synthesis stage. We further propose a clustering heuristic probability that can aid decision making in clustering and can significantly accelerate the search for the best integrated solvent-process systems. The presented method is illustrated with case studies in the design of solvents for liquid-liquid extraction, gas-absorption and extractive distillation systems.

Original languageEnglish
Pages (from-to)6316-6336
Number of pages21
JournalChemical Engineering Science
Volume61
Issue number19
DOIs
Publication statusPublished - Oct 2006
Externally publishedYes

Fingerprint

Process Design
Process design
Clustering
Synthesis
Molecules
Liquid
Gas absorption
Distillation
Liquids
Compact Group
Multiobjective optimization
Multi-objective Optimization
Accelerate
Partitioning
Absorption
Decision making
Decision Making
Design

Keywords

  • Clustering
  • Extractive distillation
  • Gas-absorption
  • Liquid-liquid extraction
  • Process synthesis
  • Solvent design

ASJC Scopus subject areas

  • Chemical Engineering(all)

Cite this

Efficient integration of optimal solvent and process design using molecular clustering. / Papadopoulos, Athanasios I.; Linke, Patrick.

In: Chemical Engineering Science, Vol. 61, No. 19, 10.2006, p. 6316-6336.

Research output: Contribution to journalArticle

@article{dc9a86cb648241e2bdd439a5c7f473e7,
title = "Efficient integration of optimal solvent and process design using molecular clustering",
abstract = "We present a molecular clustering approach for the efficient incorporation of solvent design information into process synthesis in the integrated design of solvent/process systems. The approach is to be used in conjunction with an integrated solvent/process design approach where the solvent design stage utilises multi-objective optimisation in order to identify Pareto optimal solvent candidates that are subsequently evaluated in a process synthesis stage. We propose to introduce the solvent design information into the process synthesis stage through the use of molecular clusters. The partitioning of the original Pareto optimal set of solvents leads to smaller compact groups of similar solvent molecules from which representative molecules are introduced into the process synthesis model as discrete options to determine the optimal process performance associated with the optimal solvent. We investigate two clustering strategies, serial and parallel clustering, that allow to effectively exploit the solvent-process design interactions to minimise the computational demands of the process synthesis stage. We further propose a clustering heuristic probability that can aid decision making in clustering and can significantly accelerate the search for the best integrated solvent-process systems. The presented method is illustrated with case studies in the design of solvents for liquid-liquid extraction, gas-absorption and extractive distillation systems.",
keywords = "Clustering, Extractive distillation, Gas-absorption, Liquid-liquid extraction, Process synthesis, Solvent design",
author = "Papadopoulos, {Athanasios I.} and Patrick Linke",
year = "2006",
month = "10",
doi = "10.1016/j.ces.2006.06.006",
language = "English",
volume = "61",
pages = "6316--6336",
journal = "Chemical Engineering Science",
issn = "0009-2509",
publisher = "Elsevier BV",
number = "19",

}

TY - JOUR

T1 - Efficient integration of optimal solvent and process design using molecular clustering

AU - Papadopoulos, Athanasios I.

AU - Linke, Patrick

PY - 2006/10

Y1 - 2006/10

N2 - We present a molecular clustering approach for the efficient incorporation of solvent design information into process synthesis in the integrated design of solvent/process systems. The approach is to be used in conjunction with an integrated solvent/process design approach where the solvent design stage utilises multi-objective optimisation in order to identify Pareto optimal solvent candidates that are subsequently evaluated in a process synthesis stage. We propose to introduce the solvent design information into the process synthesis stage through the use of molecular clusters. The partitioning of the original Pareto optimal set of solvents leads to smaller compact groups of similar solvent molecules from which representative molecules are introduced into the process synthesis model as discrete options to determine the optimal process performance associated with the optimal solvent. We investigate two clustering strategies, serial and parallel clustering, that allow to effectively exploit the solvent-process design interactions to minimise the computational demands of the process synthesis stage. We further propose a clustering heuristic probability that can aid decision making in clustering and can significantly accelerate the search for the best integrated solvent-process systems. The presented method is illustrated with case studies in the design of solvents for liquid-liquid extraction, gas-absorption and extractive distillation systems.

AB - We present a molecular clustering approach for the efficient incorporation of solvent design information into process synthesis in the integrated design of solvent/process systems. The approach is to be used in conjunction with an integrated solvent/process design approach where the solvent design stage utilises multi-objective optimisation in order to identify Pareto optimal solvent candidates that are subsequently evaluated in a process synthesis stage. We propose to introduce the solvent design information into the process synthesis stage through the use of molecular clusters. The partitioning of the original Pareto optimal set of solvents leads to smaller compact groups of similar solvent molecules from which representative molecules are introduced into the process synthesis model as discrete options to determine the optimal process performance associated with the optimal solvent. We investigate two clustering strategies, serial and parallel clustering, that allow to effectively exploit the solvent-process design interactions to minimise the computational demands of the process synthesis stage. We further propose a clustering heuristic probability that can aid decision making in clustering and can significantly accelerate the search for the best integrated solvent-process systems. The presented method is illustrated with case studies in the design of solvents for liquid-liquid extraction, gas-absorption and extractive distillation systems.

KW - Clustering

KW - Extractive distillation

KW - Gas-absorption

KW - Liquid-liquid extraction

KW - Process synthesis

KW - Solvent design

UR - http://www.scopus.com/inward/record.url?scp=33747020965&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33747020965&partnerID=8YFLogxK

U2 - 10.1016/j.ces.2006.06.006

DO - 10.1016/j.ces.2006.06.006

M3 - Article

VL - 61

SP - 6316

EP - 6336

JO - Chemical Engineering Science

JF - Chemical Engineering Science

SN - 0009-2509

IS - 19

ER -