Parametric Characterization and Multi-Objective Optimization of Low-Pressure Abrasive Water Jets for Biofouling Removal from Net Cages Using Response Surface Methodology and the Entropy Method

Deep-sea cages are highly susceptible to biofouling due to long-term seawater immersion, which promotes the attachment and growth of marine organisms on nets, significantly reducing fish survival. To address this issue, this study explores the use of low-pressure abrasive water jets (LPAWJs) for cage fouling removal through numerical simulation. Based on a Box–Behnken response surface design, nozzle inlet pressure X₁, nozzle outlet diameter X₂, and target distance X₃ were selected as optimization parameters. The peak jet impact force Z₁, stable jet impact force Z₂, peak abrasive water jet velocity Z₃, and peak abrasive particle velocity Z₄ were chosen as evaluation indicators to characterize the jet’s instantaneous impact ability, sustained action ability, and dynamic particle behavior. Using the entropy method, weights for each indicator were determined, and the jet’s overall removal capability was calculated. A regression model was developed by integrating numerical simulation with the response surface methodology (RSM), and the optimal parameter combination was identified as X₁ = 4.5 MPa, X₂ = 10 mm, and X₃ = 205.396 mm. Compared with the poorest experimental condition (Condition 1), the jet’s overall removal capability obtained under the optimal parameter combination increases by 101.35%. Experimental validation further confirms that the optimized parameters yield the best oyster-removal performance of the low-pressure abrasive jet, with the average removal rate improving by 100.55% relative to Condition 1. The methodology and results of this study provide a theoretical foundation and technical reference for the design and optimization of automated net-cleaning systems or net-cleaning robots equipped with low-pressure abrasive jets. By integrating the proposed model and operating parameters, future robotic systems will be able to predict and dynamically adjust jet conditions according to fouling characteristics, thereby improving the efficiency, cost-effectiveness, and sustainability of maintenance operations in marine aquaculture.