A comprehensive study on noise reduction methods of marine propellers and design procedures

Ebrahimi, Abbas; Razaghian, A.H.; Seif, Mohammad Saeed; Zahedi, Fatemeh; Nouri-Borujerdi, A.

doi:10.1016/j.apacoust.2018.12.004

Cited by 36 publications

(10 citation statements)

References 15 publications

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“…Cai et al [15] proposed an improved particle swarm optimisation algorithm, combined with an unsteady hydrodynamic performance prediction, to optimise a propeller skew distribution. Ebrahimi et al [16] studied the effects of skew angles on noise, and recommended a skew angle of 45 • to 60 • . However, they did not study the optimisation of skew distribution, which is more important for practical applications.…”

Section: Low-frequency Ds Force Optimisationmentioning

confidence: 99%

Evolutionary Optimisation for Reduction of the Low-Frequency Discrete-Spectrum Force of Marine Propeller Based on a Data-Driven Surrogate Model

Jiang

Yang

Ren

et al. 2020

JMSE

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For practical problems with non-convex, large-scale and highly constrained characteristics, evolutionary optimisation algorithms are widely used. However, advanced data-driven methods have yet to be comprehensively applied in related fields. In this study, a surrogate model combined with the Non-dominated Sorting Genetic Algorithm II-Differential Evolution (NSGA-II-DE) is applied to reduce the low-frequency Discrete-Spectrum (DS) force of propeller noise. Reduction of this force has drawn a lot of attention as it is the primary signal used in the sonar-based detection and identification of ships. In the present study, a surrogate model is proposed based on a trained Back-Propagation (BP) fully connected neural network, which improves the optimisation efficiency. The neural network is designed by analysing the depth and width of the hidden layers. The results indicate that a four-layer neural network with 64, 128, 256 and 64 nodes in each layer, respectively, exhibits the highest prediction accuracy. The prediction errors for the first order of DST, second order of DST and the thrust coefficient are only 0.21%, 5.71% and 0.01%, respectively. Data-Driven Evolutionary Optimisation (DDEO) is applied to a standard high-skew propeller to reduce DST. DDEO and a Traditional Evolutionary Optimisation Method (TEOM) obtain the same optimisation results, while the time cost of DDEO is only 0.68% that of the TEOM. Thus, the proposed DDEO is applicable to complex engineering problems in various fields.

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Section: Low-frequency Ds Force Optimisationmentioning

confidence: 99%

Evolutionary Optimisation for Reduction of the Low-Frequency Discrete-Spectrum Force of Marine Propeller Based on a Data-Driven Surrogate Model

Jiang

Yang

Ren

et al. 2020

JMSE

View full text Add to dashboard Cite

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“…The skew angle is defined as the angle between the propeller reference line and a line drawn through the shaft center line and mid-chord point of the last section of the propeller [14].…”

Section: Skew Anglementioning

confidence: 99%

Hydro-Acoustic and Hydrodynamic Optimization of a Marine Propeller Using Genetic Algorithm, Boundary Element Method, and FW-H Equations

Ebrahimi

Seif

Nouri-Borujerdi

2019

JMSE

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Noise generated by ships is one of the most significant noises in seas, and the propeller has a significant impact on the noise of ships, which reducing it can significantly lower the noise of vessels. In this study, a genetic algorithm was used to optimize the hydro-acoustic and hydrodynamic performance of propellers. The main objectives of this optimization were to reduce the propeller noise and increase its hydrodynamic efficiency. Modifying the propeller geometry is one of the most effective methods for optimizing a propeller performance. One of the numerical methods for calculating propeller noise is the Ffowcs Williams and Hawkings (FW-H) Model. A numerical code was developed by authors which solved these equations using the velocity and pressure distribution around the propeller and calculated its noise. To obtain flow quantities and to investigate the hydrodynamic performance of the propeller, a code was developed using a Boundary Element Method, the panel method. The geometry of DTMB 4119 propeller was selected for optimization, where geometric modifications included skew angle, rake angle, pitch to diameter (P/D) distribution, and chord to diameter (c/D) distribution. Finally, the results of geometric optimization were presented as Pareto optimal solutions. The results indicated that the optimum geometries had rake angles between 8.14 and 12.05 degrees and skew angles between 31.52 and 39.74 degrees. It was also observed that the increase in the chord up to a specific limit enhanced the efficiency and reduced the noise of the propeller.

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“…The noise generated by the propeller is one of the most important components of the vessels noise [6]. Therefore, measuring and calculating the propeller noise is one of the interesting research subjects in naval engineering.…”

Section: Noise Of Dtmb 4119 Propellermentioning

confidence: 99%

“…noise [6]. Therefore, measuring and calculating the propeller noise is one of the interesting research subjects in naval engineering.…”

Section: Noise Of Dtmb 4119 Propellermentioning

confidence: 99%

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Hydrodynamic and Acoustic Performance Analysis of Marine Propellers by Combination of Panel Method and FW-H Equations

Ebrahimi

Seif

Nouri-Borujerdi

2019

MCA

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The noise emitted by ships is one of the most important noises in the ocean, and the propeller noise is one of the major components of the ship noise. Measuring the propeller noise in a laboratory, despite the high accuracy and good reliability, has high costs and is very time-consuming. For this reason, the calculation of propeller noise using numerical methods has been considered in recent years. In this study, the noise of a propeller in non-cavitating conditions is calculated by the combination of the panel method (boundary element method) and solving the Ffowcs Williams-Hawkings (FW-H) equations. In this study, a panel method code is developed, and the results are validated by the experimental results of the model tests carried out in the cavitation tunnel of the Sharif University of Technology. Software for numerical calculation of propeller noise, based on FW-H equations, is also developed and the results are validated by experimental results. This study shows that the results of the panel method code have good agreement with experimental results, and that the maximum error of this code for the thrust and torque coefficients is 4% and 7%, respectively. The results of the FW-H noise code are also in good agreement with the experimental data.

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A comprehensive study on noise reduction methods of marine propellers and design procedures

Cited by 36 publications

References 15 publications

Evolutionary Optimisation for Reduction of the Low-Frequency Discrete-Spectrum Force of Marine Propeller Based on a Data-Driven Surrogate Model

Evolutionary Optimisation for Reduction of the Low-Frequency Discrete-Spectrum Force of Marine Propeller Based on a Data-Driven Surrogate Model

Hydro-Acoustic and Hydrodynamic Optimization of a Marine Propeller Using Genetic Algorithm, Boundary Element Method, and FW-H Equations

Hydrodynamic and Acoustic Performance Analysis of Marine Propellers by Combination of Panel Method and FW-H Equations

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