Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach

Autores
de Cesaro, João P. V.; Ravagnani, Mauro A. S. S.; Mele, Fernando Daniel; Costa, Caliane B. B.
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Pre-heat trains (PHTs) significantly reduce refinery fuel consumption and carbon emissions. However, these benefits are diminished by fouling in heat exchangers (HEXs). Current methods for optimizing cleaning schedules often report high computation times due to the transient nature of the fouling process and do not consider shell-side fouling, which can be significant for some oil fractions. This paper addresses these issues by adding shell-side fouling to the model and by transforming cleaning time variables into integers, reducing the problem of optimizing cleaning schedules to an integer nonlinear programming (INLP) problem. The reformulated problem is solved using integer particle swarm optimization (PSO) coupled with a simple search strategy, where the number of cleaning actions is preset and their timing is optimized. The adopted approach achieved up to 84% lower computation times compared to previous ones. Additionally, the relationship between cleaning actions and PHT performance is nonlinear, with diminishing returns from additional cleaning, and optimal cleaning schedules are often asymmetric for different HEXs within the same PHT. The proposed approach effectively reduces operating costs and provides a framework for future optimization enhancements.
Fil: de Cesaro, João P. V.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; Brasil
Fil: Ravagnani, Mauro A. S. S.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; Brasil
Fil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina
Fil: Costa, Caliane B. B.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; Brasil
Materia
HEAT EXCHANGER
PARTICLE SWARM OPTIMIZATION
FOULING
AGING
SCHEDULING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/258200
Acceder
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spelling Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approachde Cesaro, João P. V.Ravagnani, Mauro A. S. S.Mele, Fernando DanielCosta, Caliane B. B.HEAT EXCHANGERPARTICLE SWARM OPTIMIZATIONFOULINGAGINGSCHEDULINGhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2Pre-heat trains (PHTs) significantly reduce refinery fuel consumption and carbon emissions. However, these benefits are diminished by fouling in heat exchangers (HEXs). Current methods for optimizing cleaning schedules often report high computation times due to the transient nature of the fouling process and do not consider shell-side fouling, which can be significant for some oil fractions. This paper addresses these issues by adding shell-side fouling to the model and by transforming cleaning time variables into integers, reducing the problem of optimizing cleaning schedules to an integer nonlinear programming (INLP) problem. The reformulated problem is solved using integer particle swarm optimization (PSO) coupled with a simple search strategy, where the number of cleaning actions is preset and their timing is optimized. The adopted approach achieved up to 84% lower computation times compared to previous ones. Additionally, the relationship between cleaning actions and PHT performance is nonlinear, with diminishing returns from additional cleaning, and optimal cleaning schedules are often asymmetric for different HEXs within the same PHT. The proposed approach effectively reduces operating costs and provides a framework for future optimization enhancements.Fil: de Cesaro, João P. V.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; BrasilFil: Ravagnani, Mauro A. S. S.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; BrasilFil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Costa, Caliane B. B.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; BrasilMDPI2024-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/258200de Cesaro, João P. V.; Ravagnani, Mauro A. S. S.; Mele, Fernando Daniel; Costa, Caliane B. B.; Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach; MDPI; Energies; 18; 1; 12-2024; 1-271996-1073CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1996-1073/18/1/71info:eu-repo/semantics/altIdentifier/doi/10.3390/en18010071info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:50:31Zoai:ri.conicet.gov.ar:11336/258200instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:50:31.438CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
title Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
spellingShingle Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
de Cesaro, João P. V.
HEAT EXCHANGER
PARTICLE SWARM OPTIMIZATION
FOULING
AGING
SCHEDULING
title_short Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
title_full Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
title_fullStr Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
title_full_unstemmed Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
title_sort Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach
dc.creator.none.fl_str_mv de Cesaro, João P. V.
Ravagnani, Mauro A. S. S.
Mele, Fernando Daniel
Costa, Caliane B. B.
author de Cesaro, João P. V.
author_facet de Cesaro, João P. V.
Ravagnani, Mauro A. S. S.
Mele, Fernando Daniel
Costa, Caliane B. B.
author_role author
author2 Ravagnani, Mauro A. S. S.
Mele, Fernando Daniel
Costa, Caliane B. B.
author2_role author
author
author
dc.subject.none.fl_str_mv HEAT EXCHANGER
PARTICLE SWARM OPTIMIZATION
FOULING
AGING
SCHEDULING
topic HEAT EXCHANGER
PARTICLE SWARM OPTIMIZATION
FOULING
AGING
SCHEDULING
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Pre-heat trains (PHTs) significantly reduce refinery fuel consumption and carbon emissions. However, these benefits are diminished by fouling in heat exchangers (HEXs). Current methods for optimizing cleaning schedules often report high computation times due to the transient nature of the fouling process and do not consider shell-side fouling, which can be significant for some oil fractions. This paper addresses these issues by adding shell-side fouling to the model and by transforming cleaning time variables into integers, reducing the problem of optimizing cleaning schedules to an integer nonlinear programming (INLP) problem. The reformulated problem is solved using integer particle swarm optimization (PSO) coupled with a simple search strategy, where the number of cleaning actions is preset and their timing is optimized. The adopted approach achieved up to 84% lower computation times compared to previous ones. Additionally, the relationship between cleaning actions and PHT performance is nonlinear, with diminishing returns from additional cleaning, and optimal cleaning schedules are often asymmetric for different HEXs within the same PHT. The proposed approach effectively reduces operating costs and provides a framework for future optimization enhancements.
Fil: de Cesaro, João P. V.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; Brasil
Fil: Ravagnani, Mauro A. S. S.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; Brasil
Fil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina
Fil: Costa, Caliane B. B.. Universidade Estadual de Maringá. Departamento de Engenharia Química.; Brasil
description Pre-heat trains (PHTs) significantly reduce refinery fuel consumption and carbon emissions. However, these benefits are diminished by fouling in heat exchangers (HEXs). Current methods for optimizing cleaning schedules often report high computation times due to the transient nature of the fouling process and do not consider shell-side fouling, which can be significant for some oil fractions. This paper addresses these issues by adding shell-side fouling to the model and by transforming cleaning time variables into integers, reducing the problem of optimizing cleaning schedules to an integer nonlinear programming (INLP) problem. The reformulated problem is solved using integer particle swarm optimization (PSO) coupled with a simple search strategy, where the number of cleaning actions is preset and their timing is optimized. The adopted approach achieved up to 84% lower computation times compared to previous ones. Additionally, the relationship between cleaning actions and PHT performance is nonlinear, with diminishing returns from additional cleaning, and optimal cleaning schedules are often asymmetric for different HEXs within the same PHT. The proposed approach effectively reduces operating costs and provides a framework for future optimization enhancements.
publishDate 2024
dc.date.none.fl_str_mv 2024-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/258200
de Cesaro, João P. V.; Ravagnani, Mauro A. S. S.; Mele, Fernando Daniel; Costa, Caliane B. B.; Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach; MDPI; Energies; 18; 1; 12-2024; 1-27
1996-1073
CONICET Digital
CONICET
url http://hdl.handle.net/11336/258200
identifier_str_mv de Cesaro, João P. V.; Ravagnani, Mauro A. S. S.; Mele, Fernando Daniel; Costa, Caliane B. B.; Cleaning Schedule Optimization of Heat Exchangers with Fouling on Tube and Shell Sides: A Metaheuristic Approach; MDPI; Energies; 18; 1; 12-2024; 1-27
1996-1073
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1996-1073/18/1/71
info:eu-repo/semantics/altIdentifier/doi/10.3390/en18010071
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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