Multi-objective Optimisation of Marine Propellers
Real world problems have usually multiple objectives. These objective functions are of- ten in conflict, making them highly challenging in terms of determining optimal solutions and analysing solutions obtained. In this work Multi-objective Particle Swarm Optimisation (MOPSO) is employed to optimise...
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ftgriffithuniv:oai:research-repository.griffith.edu.au:10072/104585 2024-06-23T07:54:02+00:00 Multi-objective Optimisation of Marine Propellers Mirjalili, Seyedali Lewis, Andrew Mirjalili, Seyed Ali Mohammad 2015-06-01 to 2015-06-03 Reykjavik Univ, Reykjavik, ICELAND 2015 http://hdl.handle.net/10072/104585 https://doi.org/10.1016/j.procs.2015.05.504 English eng Elsevier INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2015 COMPUTATIONAL SCIENCE AT THE GATES OF NATURE 15th Annual International Conference on Computational Science (ICCS) http://hdl.handle.net/10072/104585 1877-0509 doi:10.1016/j.procs.2015.05.504 http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2015 The Authors. Published by Elsevier B.V. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work. open access Optimisation Information and computing sciences Marine engineering Conference output 2015 ftgriffithuniv https://doi.org/10.1016/j.procs.2015.05.504 2024-05-29T00:13:09Z Real world problems have usually multiple objectives. These objective functions are of- ten in conflict, making them highly challenging in terms of determining optimal solutions and analysing solutions obtained. In this work Multi-objective Particle Swarm Optimisation (MOPSO) is employed to optimise the shape of marine propellers for the first time. The two objectives identified are maximising efficiency and minimising cavitation. Several experiments are undertaken to observe and analyse the impacts of structural parameters (shape and number of blades) and operating conditions (RPM) on both objective. The paper also investigates the negative effects of uncertainties in parameters and operating conditions on efficiency and cavitation. Firstly, the results showed that MOPSO is able to find a very accurate and uniformly distributed approximation of the true Pareto optimal front. The analysis of the results also shows that a propeller with 5 or 6 blades operating between 180 and 190 RPM results in the best trade-offs for efficiency and cavitation. Secondly, the simulation results show the significant negative impacts of uncertainties on both objectives. Griffith Sciences, School of Information and Communication Technology Full Text Conference Object Iceland Griffith University: Griffith Research Online Griffith ENVELOPE(-155.500,-155.500,-85.883,-85.883) Procedia Computer Science 51 2247 2256 |
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Open Polar |
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Griffith University: Griffith Research Online |
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ftgriffithuniv |
language |
English |
topic |
Optimisation Information and computing sciences Marine engineering |
spellingShingle |
Optimisation Information and computing sciences Marine engineering Mirjalili, Seyedali Lewis, Andrew Mirjalili, Seyed Ali Mohammad Multi-objective Optimisation of Marine Propellers |
topic_facet |
Optimisation Information and computing sciences Marine engineering |
description |
Real world problems have usually multiple objectives. These objective functions are of- ten in conflict, making them highly challenging in terms of determining optimal solutions and analysing solutions obtained. In this work Multi-objective Particle Swarm Optimisation (MOPSO) is employed to optimise the shape of marine propellers for the first time. The two objectives identified are maximising efficiency and minimising cavitation. Several experiments are undertaken to observe and analyse the impacts of structural parameters (shape and number of blades) and operating conditions (RPM) on both objective. The paper also investigates the negative effects of uncertainties in parameters and operating conditions on efficiency and cavitation. Firstly, the results showed that MOPSO is able to find a very accurate and uniformly distributed approximation of the true Pareto optimal front. The analysis of the results also shows that a propeller with 5 or 6 blades operating between 180 and 190 RPM results in the best trade-offs for efficiency and cavitation. Secondly, the simulation results show the significant negative impacts of uncertainties on both objectives. Griffith Sciences, School of Information and Communication Technology Full Text |
format |
Conference Object |
author |
Mirjalili, Seyedali Lewis, Andrew Mirjalili, Seyed Ali Mohammad |
author_facet |
Mirjalili, Seyedali Lewis, Andrew Mirjalili, Seyed Ali Mohammad |
author_sort |
Mirjalili, Seyedali |
title |
Multi-objective Optimisation of Marine Propellers |
title_short |
Multi-objective Optimisation of Marine Propellers |
title_full |
Multi-objective Optimisation of Marine Propellers |
title_fullStr |
Multi-objective Optimisation of Marine Propellers |
title_full_unstemmed |
Multi-objective Optimisation of Marine Propellers |
title_sort |
multi-objective optimisation of marine propellers |
publisher |
Elsevier |
publishDate |
2015 |
url |
http://hdl.handle.net/10072/104585 https://doi.org/10.1016/j.procs.2015.05.504 |
op_coverage |
2015-06-01 to 2015-06-03 Reykjavik Univ, Reykjavik, ICELAND |
long_lat |
ENVELOPE(-155.500,-155.500,-85.883,-85.883) |
geographic |
Griffith |
geographic_facet |
Griffith |
genre |
Iceland |
genre_facet |
Iceland |
op_relation |
INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2015 COMPUTATIONAL SCIENCE AT THE GATES OF NATURE 15th Annual International Conference on Computational Science (ICCS) http://hdl.handle.net/10072/104585 1877-0509 doi:10.1016/j.procs.2015.05.504 |
op_rights |
http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2015 The Authors. Published by Elsevier B.V. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work. open access |
op_doi |
https://doi.org/10.1016/j.procs.2015.05.504 |
container_title |
Procedia Computer Science |
container_volume |
51 |
container_start_page |
2247 |
op_container_end_page |
2256 |
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1802645977413189632 |