Multi-objective optimisation of marine propellers

Seyedali Mirjalili; Andrew Lewis; Seyed Ali Mohammad Mirjalili

doi:10.1016/j.procs.2015.05.504

Multi-objective optimisation of marine propellers

Seyedali Mirjalili
, Andrew Lewis
, Seyed Ali Mohammad Mirjalili

Research output: Contribution to journal › Conference article › peer-review

42 Citations (Scopus)

Abstract

Real world problems have usually multiple objectives. These objective functions are often 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.

Original language	English
Pages (from-to)	2247-2256
Number of pages	10
Journal	Procedia Computer Science
Volume	51
Issue number	1
DOIs	https://doi.org/10.1016/j.procs.2015.05.504
Publication status	Published - 1 Jan 2015
Externally published	Yes
Event	International Conference on Computational Science, ICCS 2002 - Amsterdam, Netherlands Duration: 21 Apr 2002 → 24 Apr 2002

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production
SDG 13 Climate Action
SDG 17 Partnerships for the Goals

Keywords

Cavitation
Efficiency
Marine propeller design
MOPSO
Multi-objective Particle Swarm Optimisation

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10.1016/j.procs.2015.05.504

Cite this

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title = "Multi-objective optimisation of marine propellers",

abstract = "Real world problems have usually multiple objectives. These objective functions are often 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.",

keywords = "Cavitation, Efficiency, Marine propeller design, MOPSO, Multi-objective Particle Swarm Optimisation",

author = "Seyedali Mirjalili and Andrew Lewis and Mirjalili, \{Seyed Ali Mohammad\}",

year = "2015",

month = jan,

day = "1",

doi = "10.1016/j.procs.2015.05.504",

language = "English",

volume = "51",

pages = "2247--2256",

journal = "Procedia Computer Science",

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number = "1",

note = "International Conference on Computational Science, ICCS 2002 ; Conference date: 21-04-2002 Through 24-04-2002",

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TY - JOUR

T1 - Multi-objective optimisation of marine propellers

AU - Mirjalili, Seyedali

AU - Lewis, Andrew

AU - Mirjalili, Seyed Ali Mohammad

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Real world problems have usually multiple objectives. These objective functions are often 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.

AB - Real world problems have usually multiple objectives. These objective functions are often 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.

KW - Cavitation

KW - Efficiency

KW - Marine propeller design

KW - MOPSO

KW - Multi-objective Particle Swarm Optimisation

UR - https://www.scopus.com/pages/publications/84939196851

U2 - 10.1016/j.procs.2015.05.504

DO - 10.1016/j.procs.2015.05.504

M3 - Conference article

AN - SCOPUS:84939196851

SN - 1877-0509

VL - 51

SP - 2247

EP - 2256

JO - Procedia Computer Science

JF - Procedia Computer Science

IS - 1

T2 - International Conference on Computational Science, ICCS 2002

Y2 - 21 April 2002 through 24 April 2002

ER -

Multi-objective optimisation of marine propellers

Abstract

UN SDGs

Keywords

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