Hydro-acoustic optimization of propellers: A review of design methods

被引:3
作者
Portillo-Juan, Adrian [1 ]
Saettone, Simone [2 ]
Andersen, Poul [3 ]
Ferrer, Esteban [4 ,5 ]
机构
[1] Univ Politecn Madrid, CEHINAV Canal Ensayos Hidrodinam ETSI Navales, Ave Memoria 4, Madrid 28040, Spain
[2] Bound4blue, C Marie Curie 2,nave 14, Barbera Del Valles 08210, Barcelona, Spain
[3] Tech Univ Denmark, Dept Civil & Mech Engn, DTU, Koppels Alle 403,115, DK-2800 Lyngby, Denmark
[4] Univ Politecn Madrid, Sch Aeronaut, ETSIAE UPM, Plaza Cardenal Cisneros 3, Madrid 28040, Spain
[5] Univ Politecn Madrid, Ctr Computat Simulat, Campus Montegancedo, Boadilla Del Monte 28660, Madrid, Spain
关键词
Propeller noise; Ffowcs-Williams and Hawkings; Optimization; Hydro-acoustics; Transfer function; Neural networks; UNDERWATER NOISE ASSESSMENT; CAVITATION TUNNEL TESTS; MARINE PROPELLER; RADIATED NOISE; PREDICTION; PART; MODEL; FLOW; SHIP; VALIDATION;
D O I
10.1016/j.apor.2024.104158
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
In recent years, the escalation of anthropogenic noise within marine environments has become a pressing ecological concern. Despite the proliferation of guidelines aimed at mitigating this issue, their adoption remains non-compulsory. The International Maritime Organization (IMO) advocates for noise reduction through the refinement of propeller design and heightened research to curtail acoustic emissions, ensuring that such measures do not compromise propulsive efficiency. This review delves into the array of strategies devised to attenuate noise pollution. It scrutinizes the methodologies employed to evaluate the hydroacoustic attributes of propellers, including experimental and computational approaches. Furthermore, it summarizes the techniques employed in the multiobjective optimization of propellers, which involves balancing the maximization of efficiency against the minimization of noise emission. The findings highlight the necessity for a comprehensive, interdisciplinary approach to the hydroacoustic optimization of marine propellers, encompassing cavitation experiments and advanced numerical simulations. In the field of propeller optimization, the traditional reliance on genetic algorithms is giving way to the adoption of neural networks and surrogate models derived from computational fluid dynamics data, particularly when addressing complex, nonlinear phenomena such as hydro-acoustics and cavitation.
引用
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页数:25
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