A novel standpoint of Pressure Swing Adsorption processes multi-objective optimization: An approach based on feasible operation region mapping

•A new approach for multi-objective optimization of Pressure Swing Adsorption.•Fisher–Snedecor test to the solution of a multi-objective problem is deduced.•The concept of Feasible Operating Regions is presented to address the study case.•The obtained Pareto region is divided into operating sub-regi...

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Veröffentlicht in:Chemical engineering research & design 2022-02, Vol.178, p.590-601, Article 590
Hauptverfasser: Rebello, Carine M., Martins, Márcio A.F., Rodrigues, Alírio E., Loureiro, José M., Ribeiro, Ana M., Nogueira, Idelfonso B.R.
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container_end_page 601
container_issue
container_start_page 590
container_title Chemical engineering research & design
container_volume 178
creator Rebello, Carine M.
Martins, Márcio A.F.
Rodrigues, Alírio E.
Loureiro, José M.
Ribeiro, Ana M.
Nogueira, Idelfonso B.R.
description •A new approach for multi-objective optimization of Pressure Swing Adsorption.•Fisher–Snedecor test to the solution of a multi-objective problem is deduced.•The concept of Feasible Operating Regions is presented to address the study case.•The obtained Pareto region is divided into operating sub-regions clustering. Optimization of cyclic adsorption processes is a challenging issue due to the dynamic-operating complexity of these processes. In this context, this work proposes a new approach for multi-objective optimization of Pressure Swing Adsorption (PSA) units, extending the concept of the Pareto front to Pareto region. The proposed methodology, hitherto unexplored in the literature, consists of integrating a likelihood test, an arrangement from the Fisher–Snedecor test to the solution of a multi-objective problem provided by a Swarm Particle Optimization technique. The Pareto region is divided into operating sub-regions that meet the optimization constraints and prioritize a determined objective by a clustering process. These sub-regions make the operation more flexible. Furthermore, the analysis of the operating variables feasible operation interval demonstrated to be an important tool to provide information regarding the system behavior. As a study case, it is presented the optimization of a PSA process for syngas purification. The results demonstrate that the methodology proposed here uses the feasible operation region map and the clustering strategy to exploit the multi-objective optimization. Therefore, providing a more reliable and precise optimization of PSA units, while providing an important tool for making decisions in the PSA system.
doi_str_mv 10.1016/j.cherd.2021.12.047
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Optimization of cyclic adsorption processes is a challenging issue due to the dynamic-operating complexity of these processes. In this context, this work proposes a new approach for multi-objective optimization of Pressure Swing Adsorption (PSA) units, extending the concept of the Pareto front to Pareto region. The proposed methodology, hitherto unexplored in the literature, consists of integrating a likelihood test, an arrangement from the Fisher–Snedecor test to the solution of a multi-objective problem provided by a Swarm Particle Optimization technique. The Pareto region is divided into operating sub-regions that meet the optimization constraints and prioritize a determined objective by a clustering process. These sub-regions make the operation more flexible. Furthermore, the analysis of the operating variables feasible operation interval demonstrated to be an important tool to provide information regarding the system behavior. As a study case, it is presented the optimization of a PSA process for syngas purification. The results demonstrate that the methodology proposed here uses the feasible operation region map and the clustering strategy to exploit the multi-objective optimization. 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Optimization of cyclic adsorption processes is a challenging issue due to the dynamic-operating complexity of these processes. In this context, this work proposes a new approach for multi-objective optimization of Pressure Swing Adsorption (PSA) units, extending the concept of the Pareto front to Pareto region. The proposed methodology, hitherto unexplored in the literature, consists of integrating a likelihood test, an arrangement from the Fisher–Snedecor test to the solution of a multi-objective problem provided by a Swarm Particle Optimization technique. The Pareto region is divided into operating sub-regions that meet the optimization constraints and prioritize a determined objective by a clustering process. These sub-regions make the operation more flexible. Furthermore, the analysis of the operating variables feasible operation interval demonstrated to be an important tool to provide information regarding the system behavior. 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subjects Adsorption
Clustering
Feasible operation region assessment
Multi-objective optimization
Multiple objective analysis
Optimization
Pareto optimization
Pareto optimum
Particle Swarm Optimization
Pressure Swing Adsorption
Syngas purification
Synthesis gas
title A novel standpoint of Pressure Swing Adsorption processes multi-objective optimization: An approach based on feasible operation region mapping
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