Optimization Design of Steel Ladle Refractory Lining Structure Based on <scp>NSGA</scp> ‐ <scp>II</scp> Algorithm

ABSTRACT The NSGA‐II algorithm is widely applied in multiobjective mechanical structure optimization. In this study, the NSGA‐II algorithm was adopted to optimize the refractory lining structure of a ladle. First, a parametric model of the ladle was established using ANSYS Workbench, and the temperature and stress fields under typical operating conditions were calculated to generate the sample data required for training a BPNN prediction model. Second, to address the limitations of conventional BPNN, a genetic algorithm was employed to optimize the initial weights and thresholds. Taking the thicknesses of the working layer, permanent layer, and insulation layer as design variables, a GA‐BPNN single‐objective prediction model was developed, enabling high‐precision predictions of ladle mass, ladle volume, maximum ladle shell temperature, and maximum refractory lining stress. Finally, the NSGA‐II algorithm was utilized to solve the multiobjective optimization problem of the ladle refractory lining. In this optimization, ladle mass and capacity were imposed as constraints, while the maximum shell temperature and maximum lining stress were defined as objectives. In the simulation experiments, thermo‐mechanical coupling analysis was performed in ANSYS Workbench to generate 81 training samples and 10 test samples of temperature and stress data. The GA‐BPNN model optimized by the genetic algorithm achieved accurate predictions of ladle mass, volume, shell temperature rise, and lining stress. The results demonstrated that when the insulation, permanent, and working layers were 9.992, 83.998, and 137 mm thick, respectively, the ladle mass, volume, maximum shell temperature, and maximum lining stress reached 57,972.525 kg, 14.298 m 3 , 145.549°C, and 43.621 MPa. Under this parameter combination, the ladle exhibited optimal comprehensive performance in terms of insulation and service life. This method provides an effective approach to determining the optimal refractory lining structure of ladles, with significant implications for improving thermal performance, extending service life, and enhancing industrial economic efficiency.