Multi-objective Optimisation of Marine Propellers

View/ Open
File version
Version of Record (VoR)
Author(s)
Mirjalili, Seyedali
Lewis, Andrew
Mirjalili, Seyed Ali Mohammad
Year published
2015
Metadata
Show full item recordAbstract
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 ...
View more >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.
View less >
View more >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.
View less >
Conference Title
INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2015 COMPUTATIONAL SCIENCE AT THE GATES OF NATURE
Volume
51
Issue
1
Copyright Statement
© 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.
Subject
Optimisation
Information and computing sciences
Marine engineering