Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design

A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. The Pareto solutions of the sin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Energy (Oxford) 2023-01, Vol.262, p.125271, Article 125271
Hauptverfasser: Santos, Lucas F., Costa, Caliane B.B., Caballero, José A., Ravagnani, Mauro A.S.S.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page 125271
container_title Energy (Oxford)
container_volume 262
creator Santos, Lucas F.
Costa, Caliane B.B.
Caballero, José A.
Ravagnani, Mauro A.S.S.
description A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. The Pareto solutions of the single-mixed refrigerant (SMR) and propane-precooled mixed refrigerant (C3MR) processes are compared to determine the suitability of each process in terms of energy consumption and heat exchanger area. Kriging models and the ɛ-constraint methodology are used to sequentially provide simple surrogate optimization subproblems, whose minimizers are promising feasible and non-dominated solutions to the original black-box problem. The surrogate-based ɛ-constrained optimization subproblems are solved in GAMS using CONOPT. The Pareto Fronts achieved with the surrogate-based framework dominate the results from the NSGA-II, a well-established meta-heuristics of multi-objective optimization. The objective functions of non-dominated solutions go as low as 1045 and 980.3 kJ/kg-LNG and specific UA values of 212.2 and 266.9 kJ/(°C kg-LNG) for SMR and C3MR, respectively. The trade-off solutions that present the minimum sum of relative objectives are analyzed as well as the dominance of C3MR over SMR at low power consumption values and conversely at low heat exchanger area utilization. [Display omitted] •SMR and C3MR processes are designed to minimize usage of power and heat transfer area.•First application of multi-objective surrogate-based optimization to LNG processes.•Pareto Fronts surpass the state-of-the-art multi-objective meta-heuristics of NSGA-II.•Appropriate trade-off solutions of conflicting objectives are derived and analyzed.•Pareto solutions of SMR and C3MR processes are compared to derive their suitability.
doi_str_mv 10.1016/j.energy.2022.125271
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2723118366</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0360544222021569</els_id><sourcerecordid>2723118366</sourcerecordid><originalsourceid>FETCH-LOGICAL-c385t-88d0197ad64eb1d4a99df5ad93faaf5df1b64d91f8503fed8b736a858d8c5b5a3</originalsourceid><addsrcrecordid>eNp9kM9u1DAQh3MAif7hDTj4yCWLncRZ54JUVS1FWtQLnK2JPY5mceJgOyttT30H3pAnIW04cxqN9Pt9M_qK4oPgO8FF--m4wwnjcN5VvKp2opLVXrwpLnjd8lI2TfWuuEzpyDmXqusuivO3xWcqQ39Ek-mELNG4eMgUpj_Pv8OcaaSn15WdCNjPSANNA0tLjGGAjGwMFn1iMM-e0LIc2AR5ieDZAIl5-rWgA_MKmGMwmBKzmGiYrou3DnzC9__mVfHj_u777UN5ePzy9fbmUJpayVwqZbno9mDbBnthG-g66yTYrnYATlon-raxnXBK8tqhVf2-bkFJZZWRvYT6qvi4cdfz6zMp65GSQe9hwrAkXe2rWghVt-0abbaoiSGliE7PkUaIZy24frGrj3qzq1_s6s3uWvu81VYReCKMOhnCyaCluFrVNtD_AX8BMceMuA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2723118366</pqid></control><display><type>article</type><title>Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design</title><source>Elsevier ScienceDirect Journals Complete - AutoHoldings</source><creator>Santos, Lucas F. ; Costa, Caliane B.B. ; Caballero, José A. ; Ravagnani, Mauro A.S.S.</creator><creatorcontrib>Santos, Lucas F. ; Costa, Caliane B.B. ; Caballero, José A. ; Ravagnani, Mauro A.S.S.</creatorcontrib><description>A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. The Pareto solutions of the single-mixed refrigerant (SMR) and propane-precooled mixed refrigerant (C3MR) processes are compared to determine the suitability of each process in terms of energy consumption and heat exchanger area. Kriging models and the ɛ-constraint methodology are used to sequentially provide simple surrogate optimization subproblems, whose minimizers are promising feasible and non-dominated solutions to the original black-box problem. The surrogate-based ɛ-constrained optimization subproblems are solved in GAMS using CONOPT. The Pareto Fronts achieved with the surrogate-based framework dominate the results from the NSGA-II, a well-established meta-heuristics of multi-objective optimization. The objective functions of non-dominated solutions go as low as 1045 and 980.3 kJ/kg-LNG and specific UA values of 212.2 and 266.9 kJ/(°C kg-LNG) for SMR and C3MR, respectively. The trade-off solutions that present the minimum sum of relative objectives are analyzed as well as the dominance of C3MR over SMR at low power consumption values and conversely at low heat exchanger area utilization. [Display omitted] •SMR and C3MR processes are designed to minimize usage of power and heat transfer area.•First application of multi-objective surrogate-based optimization to LNG processes.•Pareto Fronts surpass the state-of-the-art multi-objective meta-heuristics of NSGA-II.•Appropriate trade-off solutions of conflicting objectives are derived and analyzed.•Pareto solutions of SMR and C3MR processes are compared to derive their suitability.</description><identifier>ISSN: 0360-5442</identifier><identifier>DOI: 10.1016/j.energy.2022.125271</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>energy ; energy use and consumption ; heat exchangers ; Kriging ; liquefaction ; Mathematical programming ; Multi-objective simulation–optimization ; natural gas ; Natural gas liquefaction ; Process design ; Surrogate-based optimization</subject><ispartof>Energy (Oxford), 2023-01, Vol.262, p.125271, Article 125271</ispartof><rights>2022 The Author(s)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-88d0197ad64eb1d4a99df5ad93faaf5df1b64d91f8503fed8b736a858d8c5b5a3</citedby><cites>FETCH-LOGICAL-c385t-88d0197ad64eb1d4a99df5ad93faaf5df1b64d91f8503fed8b736a858d8c5b5a3</cites><orcidid>0000-0001-5931-4272</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.energy.2022.125271$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,778,782,3539,27911,27912,45982</link.rule.ids></links><search><creatorcontrib>Santos, Lucas F.</creatorcontrib><creatorcontrib>Costa, Caliane B.B.</creatorcontrib><creatorcontrib>Caballero, José A.</creatorcontrib><creatorcontrib>Ravagnani, Mauro A.S.S.</creatorcontrib><title>Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design</title><title>Energy (Oxford)</title><description>A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. The Pareto solutions of the single-mixed refrigerant (SMR) and propane-precooled mixed refrigerant (C3MR) processes are compared to determine the suitability of each process in terms of energy consumption and heat exchanger area. Kriging models and the ɛ-constraint methodology are used to sequentially provide simple surrogate optimization subproblems, whose minimizers are promising feasible and non-dominated solutions to the original black-box problem. The surrogate-based ɛ-constrained optimization subproblems are solved in GAMS using CONOPT. The Pareto Fronts achieved with the surrogate-based framework dominate the results from the NSGA-II, a well-established meta-heuristics of multi-objective optimization. The objective functions of non-dominated solutions go as low as 1045 and 980.3 kJ/kg-LNG and specific UA values of 212.2 and 266.9 kJ/(°C kg-LNG) for SMR and C3MR, respectively. The trade-off solutions that present the minimum sum of relative objectives are analyzed as well as the dominance of C3MR over SMR at low power consumption values and conversely at low heat exchanger area utilization. [Display omitted] •SMR and C3MR processes are designed to minimize usage of power and heat transfer area.•First application of multi-objective surrogate-based optimization to LNG processes.•Pareto Fronts surpass the state-of-the-art multi-objective meta-heuristics of NSGA-II.•Appropriate trade-off solutions of conflicting objectives are derived and analyzed.•Pareto solutions of SMR and C3MR processes are compared to derive their suitability.</description><subject>energy</subject><subject>energy use and consumption</subject><subject>heat exchangers</subject><subject>Kriging</subject><subject>liquefaction</subject><subject>Mathematical programming</subject><subject>Multi-objective simulation–optimization</subject><subject>natural gas</subject><subject>Natural gas liquefaction</subject><subject>Process design</subject><subject>Surrogate-based optimization</subject><issn>0360-5442</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kM9u1DAQh3MAif7hDTj4yCWLncRZ54JUVS1FWtQLnK2JPY5mceJgOyttT30H3pAnIW04cxqN9Pt9M_qK4oPgO8FF--m4wwnjcN5VvKp2opLVXrwpLnjd8lI2TfWuuEzpyDmXqusuivO3xWcqQ39Ek-mELNG4eMgUpj_Pv8OcaaSn15WdCNjPSANNA0tLjGGAjGwMFn1iMM-e0LIc2AR5ieDZAIl5-rWgA_MKmGMwmBKzmGiYrou3DnzC9__mVfHj_u777UN5ePzy9fbmUJpayVwqZbno9mDbBnthG-g66yTYrnYATlon-raxnXBK8tqhVf2-bkFJZZWRvYT6qvi4cdfz6zMp65GSQe9hwrAkXe2rWghVt-0abbaoiSGliE7PkUaIZy24frGrj3qzq1_s6s3uWvu81VYReCKMOhnCyaCluFrVNtD_AX8BMceMuA</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Santos, Lucas F.</creator><creator>Costa, Caliane B.B.</creator><creator>Caballero, José A.</creator><creator>Ravagnani, Mauro A.S.S.</creator><general>Elsevier Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0001-5931-4272</orcidid></search><sort><creationdate>20230101</creationdate><title>Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design</title><author>Santos, Lucas F. ; Costa, Caliane B.B. ; Caballero, José A. ; Ravagnani, Mauro A.S.S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c385t-88d0197ad64eb1d4a99df5ad93faaf5df1b64d91f8503fed8b736a858d8c5b5a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>energy</topic><topic>energy use and consumption</topic><topic>heat exchangers</topic><topic>Kriging</topic><topic>liquefaction</topic><topic>Mathematical programming</topic><topic>Multi-objective simulation–optimization</topic><topic>natural gas</topic><topic>Natural gas liquefaction</topic><topic>Process design</topic><topic>Surrogate-based optimization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Santos, Lucas F.</creatorcontrib><creatorcontrib>Costa, Caliane B.B.</creatorcontrib><creatorcontrib>Caballero, José A.</creatorcontrib><creatorcontrib>Ravagnani, Mauro A.S.S.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Energy (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Santos, Lucas F.</au><au>Costa, Caliane B.B.</au><au>Caballero, José A.</au><au>Ravagnani, Mauro A.S.S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design</atitle><jtitle>Energy (Oxford)</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>262</volume><spage>125271</spage><pages>125271-</pages><artnum>125271</artnum><issn>0360-5442</issn><abstract>A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. The Pareto solutions of the single-mixed refrigerant (SMR) and propane-precooled mixed refrigerant (C3MR) processes are compared to determine the suitability of each process in terms of energy consumption and heat exchanger area. Kriging models and the ɛ-constraint methodology are used to sequentially provide simple surrogate optimization subproblems, whose minimizers are promising feasible and non-dominated solutions to the original black-box problem. The surrogate-based ɛ-constrained optimization subproblems are solved in GAMS using CONOPT. The Pareto Fronts achieved with the surrogate-based framework dominate the results from the NSGA-II, a well-established meta-heuristics of multi-objective optimization. The objective functions of non-dominated solutions go as low as 1045 and 980.3 kJ/kg-LNG and specific UA values of 212.2 and 266.9 kJ/(°C kg-LNG) for SMR and C3MR, respectively. The trade-off solutions that present the minimum sum of relative objectives are analyzed as well as the dominance of C3MR over SMR at low power consumption values and conversely at low heat exchanger area utilization. [Display omitted] •SMR and C3MR processes are designed to minimize usage of power and heat transfer area.•First application of multi-objective surrogate-based optimization to LNG processes.•Pareto Fronts surpass the state-of-the-art multi-objective meta-heuristics of NSGA-II.•Appropriate trade-off solutions of conflicting objectives are derived and analyzed.•Pareto solutions of SMR and C3MR processes are compared to derive their suitability.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.energy.2022.125271</doi><orcidid>https://orcid.org/0000-0001-5931-4272</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0360-5442
ispartof Energy (Oxford), 2023-01, Vol.262, p.125271, Article 125271
issn 0360-5442
language eng
recordid cdi_proquest_miscellaneous_2723118366
source Elsevier ScienceDirect Journals Complete - AutoHoldings
subjects energy
energy use and consumption
heat exchangers
Kriging
liquefaction
Mathematical programming
Multi-objective simulation–optimization
natural gas
Natural gas liquefaction
Process design
Surrogate-based optimization
title Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T03%3A50%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Multi-objective%20simulation%E2%80%93optimization%20via%20kriging%20surrogate%20models%20applied%20to%20natural%20gas%20liquefaction%20process%20design&rft.jtitle=Energy%20(Oxford)&rft.au=Santos,%20Lucas%20F.&rft.date=2023-01-01&rft.volume=262&rft.spage=125271&rft.pages=125271-&rft.artnum=125271&rft.issn=0360-5442&rft_id=info:doi/10.1016/j.energy.2022.125271&rft_dat=%3Cproquest_cross%3E2723118366%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2723118366&rft_id=info:pmid/&rft_els_id=S0360544222021569&rfr_iscdi=true