Robust simulation-based design optimization of marine propellers

被引:1
作者
Gaggero, Stefano [1 ]
机构
[1] Univ Genoa, Dept Elect Elect Telecommun Engn & Naval Architect, Via Montallegro 1, I-16145 Genoa, Italy
关键词
PANEL CODE; SHIP;
D O I
10.1016/j.oceaneng.2025.120397
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Marine propellers often function under uncertain conditions such as variable inflow, rate of revolution, and manufacturing tolerances. A deterministic design approach may result in excessive sensitivity to minor variations, leading to suboptimal performance in real-world scenarios. Then, quantifying these uncertainties, and leveraging their influence on propeller performance, is of fundamental importance to design and optimizing configurations less sensitive to input variations. In the context of a "robust" design of marine propellers through simulation-based design optimization methodologies, this paper explores both deterministic and non- deterministic design approaches for a conventional propulsor, accounting for the uncertainties in the nominal operating conditions. Since the quantification of uncertainties can be computationally very intensive, an efficient medium-fidelity Boundary Element Method (BEM) solver using equivalent steady-state cavitating analyses is employed in the optimization process. The optimal designs are finally validated through fully unsteady and cavitating BEM and RANSE calculations to demonstrate the advantages of the non-deterministic design approach.
引用
收藏
页数:23
相关论文
共 76 条
[1]  
Barrico C., 2006, 7 INT C MULT PROGR M, P565
[2]   A Two-Stage Optimisation Method for Full-Scale Marine Propellers Working Behind a Ship [J].
Berger, Stephan ;
Druckenbrod, Markus ;
Pergande, Markus ;
Abdel-Maksoud, Moustafa .
SHIP TECHNOLOGY RESEARCH, 2014, 61 (02) :64-79
[3]   CPP propeller cavitation and noise optimization at different pitches with panel code and validation by cavitation tunnel measurements [J].
Bertetta, D. ;
Brizzolara, S. ;
Gaggero, S. ;
Viviani, M. ;
Savio, L. .
OCEAN ENGINEERING, 2012, 53 :177-195
[4]   Robust optimization - A comprehensive survey [J].
Beyer, Hans-Georg ;
Sendhoff, Bernhard .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2007, 196 (33-34) :3190-3218
[5]   Efficient Sampling When Searching for Robust Solutions [J].
Branke, Juergen ;
Fei, Xin .
PARALLEL PROBLEM SOLVING FROM NATURE - PPSN XIV, 2016, 9921 :237-246
[6]   Propeller blade shape optimization for efficiency improvement [J].
Cho, JS ;
Lee, SC .
COMPUTERS & FLUIDS, 1998, 27 (03) :407-419
[7]  
Coraddu A., 2023, 10 INT C COMP METH M
[8]  
Deb K, 2005, LECT NOTES COMPUT SC, V3410, P150
[9]   Introducing robustness in multi-objective optimization [J].
Deb, Kalyanmoy ;
Gupta, Himanshu .
EVOLUTIONARY COMPUTATION, 2006, 14 (04) :463-494
[10]   A machine learning approach for propeller design and optimization: Part I [J].
Doijode, Pranav Sumanth ;
Hickel, Stefan ;
van Terwisga, Tom ;
Visser, Klaas .
APPLIED OCEAN RESEARCH, 2022, 124