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<p>Intelligent unmanned baiting boats enhance efficiency through precise baiting, reducing environmental pollution, and resource waste. In this study, the baiting boat structure was innovatively designed using an axiomatic design (AD) hierarchical analysis. In the proposed method, extracting a 3 × 3 coupling was a contradiction, and solving the contradiction between the propulsive efficiency and cavitation phenomenon was solved by the application of Extenics. The ducted propeller was optimized using non-uniform rational B-splines (NURBS) curves, delta shift for airfoil profile control, and detached eddy simulation (DES) hybrid Reynolds-averaged Navier–Stokes/large eddy simulation (RANS/LES) with shear stress transfer (SST) <i>k-ω</i> turbulence modeling. In contrast, duct profile airfoils were adjusted via non-dominated sorting genetic algorithms II (NSGA-II) to improve the hydrodynamic performance. Simulation and prototype experiments confirmed that the improved design minimizes cavitation, reduces energy consumption and equipment loss, extends service life, enhances operational reliability, aligns with green aquaculture, enhances sustainable industry development, and provides theoretical and methodological support for the design of related products.</p>

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Enhancing intelligent bait boat performance: axiomatic design and Extenics-driven optimization of ducted propellers in aquaculture applications

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月14日

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  • Xinyi Gao,
  • Jianmin Zhang,
  • Guoze Wang

摘要

Intelligent unmanned baiting boats enhance efficiency through precise baiting, reducing environmental pollution, and resource waste. In this study, the baiting boat structure was innovatively designed using an axiomatic design (AD) hierarchical analysis. In the proposed method, extracting a 3 × 3 coupling was a contradiction, and solving the contradiction between the propulsive efficiency and cavitation phenomenon was solved by the application of Extenics. The ducted propeller was optimized using non-uniform rational B-splines (NURBS) curves, delta shift for airfoil profile control, and detached eddy simulation (DES) hybrid Reynolds-averaged Navier–Stokes/large eddy simulation (RANS/LES) with shear stress transfer (SST) k-ω turbulence modeling. In contrast, duct profile airfoils were adjusted via non-dominated sorting genetic algorithms II (NSGA-II) to improve the hydrodynamic performance. Simulation and prototype experiments confirmed that the improved design minimizes cavitation, reduces energy consumption and equipment loss, extends service life, enhances operational reliability, aligns with green aquaculture, enhances sustainable industry development, and provides theoretical and methodological support for the design of related products.