Liquid propellant engine conceptual design by using a fuzzy-multi-objective genetic algorithm (MOGA) optimization method
This paper presents an extension of fuzzy-multi-objective genetic algorithm (MOGA) optimization methodology that could effectively be used to find the overall satisfaction of objective functions (selecting the design variables) in the early stages of design process. The coupling of objective functio...
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| Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering Journal of aerospace engineering, 2014-12, Vol.228 (14), p.2587-2603 |
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| container_title | Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering |
| container_volume | 228 |
| creator | Mirshams, M Naseh, H Taei, H Fazeley, HR |
| description | This paper presents an extension of fuzzy-multi-objective genetic algorithm (MOGA) optimization methodology that could effectively be used to find the overall satisfaction of objective functions (selecting the design variables) in the early stages of design process. The coupling of objective functions due to design variables in an engineering design process will result in difficulties in design optimization problems. The primary application of this methodology is the design of a liquid propellant engine with the maximum specific impulse and the minimum weight. The independent design variables in this model are combustion chamber pressure, exit pressure, oxidizer to fuel mass flow rate. To handle the mentioned problems, a fuzzy-multi-objective genetic algorithm optimization methodology is developed based on Pareto optimal set. Liquid propellant engine, F-1 is modeled to illustrate accuracy and efficiency of proposed methodology. |
| doi_str_mv | 10.1177/0954410014521390 |
| format | Article |
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Liquid propellant engine, F-1 is modeled to illustrate accuracy and efficiency of proposed methodology.</description><subject>Aerospace engineering</subject><subject>Design optimization</subject><subject>Engines</subject><subject>Fuzzy sets</subject><subject>Genetic algorithms</subject><subject>Liquid propellants</subject><subject>Mathematical models</subject><subject>Methodology</subject><subject>Minimum weight</subject><subject>Optimization</subject><subject>Oxidizers</subject><subject>Pressure</subject><issn>0954-4100</issn><issn>2041-3025</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp1kb1PwzAQxS0EEqWwM1pigSFgxx9txgrxJRWxwBy59jl1ldhp7CDav56UMqBK3HLD-93p3j2ELim5pXQyuSOF4JwSQrnIKSvIERrlhNOMkVwco9FOznb6KTqLcUWGEpKN0NfcrXtncNuFFupa-YTBV84D1sFraFOvamwgusrjxQb30fkKK2z77XaTNX2dXBYWK9DJfQKuwENyGqu6Cp1LywZfv749zW5waJNr3FYlFzxuIC2DOUcnVtURLn77GH08PrzfP2fzt6eX-9k804znKdPE5ERKY3JJGQgObDoRZCKlsMaQxYJOmbFgLZUFtaJQnAvOJGiSs4LZQrMxut7vHRyue4ipbFzUP1Yh9LGkUlDOcsrJgF4doKvQd364bqCYpIUcvjhQZE_pLsTYgS3bzjWq25SUlLsoysMohpFsPxJVBX-W_sd_A_OCiLk</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Mirshams, M</creator><creator>Naseh, H</creator><creator>Taei, H</creator><creator>Fazeley, HR</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope><scope>7SC</scope><scope>JQ2</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20141201</creationdate><title>Liquid propellant engine conceptual design by using a fuzzy-multi-objective genetic algorithm (MOGA) optimization method</title><author>Mirshams, M ; Naseh, H ; Taei, H ; Fazeley, HR</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c342t-c0d2066dd2613e54e387507665fdd0bb183dfeff1691f59a445436ec02393f9c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Aerospace engineering</topic><topic>Design optimization</topic><topic>Engines</topic><topic>Fuzzy sets</topic><topic>Genetic algorithms</topic><topic>Liquid propellants</topic><topic>Mathematical models</topic><topic>Methodology</topic><topic>Minimum weight</topic><topic>Optimization</topic><topic>Oxidizers</topic><topic>Pressure</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mirshams, M</creatorcontrib><creatorcontrib>Naseh, H</creatorcontrib><creatorcontrib>Taei, H</creatorcontrib><creatorcontrib>Fazeley, HR</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. 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| ispartof | Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering, 2014-12, Vol.228 (14), p.2587-2603 |
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| language | eng |
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| source | SAGE Complete A-Z List |
| subjects | Aerospace engineering Design optimization Engines Fuzzy sets Genetic algorithms Liquid propellants Mathematical models Methodology Minimum weight Optimization Oxidizers Pressure |
| title | Liquid propellant engine conceptual design by using a fuzzy-multi-objective genetic algorithm (MOGA) optimization method |
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