Scholarlink

<p>As is well-known, the naval thruster of a vessel must maximize the power delivered by the propulsion system and transmission line, ensuring efficient performance while avoiding undesirable phenomena such as cavitation. The proper sizing of the propulsion system during the preliminary design phase has a direct impact on fuel consumption throughout the vessel’s operational life. Over time, various methods have been developed to optimize thruster design. Metaheuristic techniques have been increasingly employed to solve complex problems with analytically intractable solutions. One such technique is <i>Particle Swarm Optimization</i> (PSO), which accelerates the research for optimal solution by leveraging information sharing among particles to accelerate the search for an optimal solution. This paper presents a methodology for the optimal sizing of B-Series (Wageningen) naval thrusters using PSO to enhance the design process. The approach determines the optimal values for the advance coefficient, blade area ratio, pitch-to-diameter ratio, and number of blades. The proposed methodology was implemented in a Python 3.8 computational code developed by the authors and applied to seven vessel cases, each using different computational optimization methods for thruster sizing. The results demonstrate that PSO yields to significant improvements in thruster efficiency, computational performance, and design time. Moreover, PSO provides a broader set of optimal solutions compared to conventional methods, underscoring its potential contributions to the field of floating systems hydrodynamics.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimization and sizing of B-Series propeller by the Particle Swarm method

  • 期刊论文

  • 发表日期：

    2025年7月8日

查看全文
  • Miguel Angel Celis Carbajal,
  • Maria Luisa Barreto de Gois,
  • Felipe Rodrigues Modesto

摘要

As is well-known, the naval thruster of a vessel must maximize the power delivered by the propulsion system and transmission line, ensuring efficient performance while avoiding undesirable phenomena such as cavitation. The proper sizing of the propulsion system during the preliminary design phase has a direct impact on fuel consumption throughout the vessel’s operational life. Over time, various methods have been developed to optimize thruster design. Metaheuristic techniques have been increasingly employed to solve complex problems with analytically intractable solutions. One such technique is Particle Swarm Optimization (PSO), which accelerates the research for optimal solution by leveraging information sharing among particles to accelerate the search for an optimal solution. This paper presents a methodology for the optimal sizing of B-Series (Wageningen) naval thrusters using PSO to enhance the design process. The approach determines the optimal values for the advance coefficient, blade area ratio, pitch-to-diameter ratio, and number of blades. The proposed methodology was implemented in a Python 3.8 computational code developed by the authors and applied to seven vessel cases, each using different computational optimization methods for thruster sizing. The results demonstrate that PSO yields to significant improvements in thruster efficiency, computational performance, and design time. Moreover, PSO provides a broader set of optimal solutions compared to conventional methods, underscoring its potential contributions to the field of floating systems hydrodynamics.