An advanced framework for the layout optimization of multi-nozzle rotary derusting sprayer using CFD-IBES methods

The spatial arrangement of multiple nozzles has a great influence on the efficiency of rotary derusting sprayers. However, the current design method for sprayers is mainly limited to a rod-like shape sprayer and relies on empirical knowledge, lacking accurate theoretical analysis and optimization framework. In this paper, an advanced framework for the layout optimization of a multi-nozzle rotary derusting sprayer using a CFD and improved bald eagle search (henceforth IBES) algorithm coupled methods was proposed to enhance the hydrodynamic performance. Firstly, the CFD method was used to study the effect of the nozzle’s technological parameters, including attack angle, standoff distance, and rotational speed on the hydrodynamic performance of water jetting, determining the optimal ranges to guide engineering practice. Then, by the motion analysis of derusting sprayer, a dual-objective optimization model was established, aiming at improving the uniformity of energy distribution and the maximum sweep width. To realize this optimization model, an IBES algorithm was proposed, which can achieve better hydrodynamics and cleaning efficiency by adjusting the multi-nozzle spatial arrangement. In order to ensure optimization accuracy, an elite opposition-based learning strategy combined with the gradient boosting optimization algorithm was adopted by the IBES algorithm. Finally, a practical experiment was implemented on the cross-shaped derusting sprayer commonly used in shipyards, demonstrating that compared with the original scheme, the proposed optimization design method is effective and feasible, and can effectively improve the rust removal efficiency by 22.8%. This study provides an effective optimization framework and a new quantification technique for the actual rotary derusting sprayer design used in the ship-repairing industries.