Internal flow analysis and multi-objective optimization of flow channel structure for aerospace component gluing actuators

In aerospace manufacturing, adhesive bonding processes are widely used, and a well-designed coater structure can contribute to a more stable glue discharge state. Therefore, this study addresses the structural optimization of gluing actuators for aerospace component panels, by integrating numerical simulation, random forest prediction models, and the Multi-Objective Ant Lion Optimization Algorithm (MOALO). The key flow-channel parameters affecting gluing uniformity and stability were systematically analyzed. Through parameter optimization, the velocity transition zone at the glue outlet was reduced by 37.5%, and the standard deviation was decreased by 23.3%, thereby improving the quality of gluing, and enabling the production of adhesive layers that meet subsequent process requirements. The research methodology adopted in this paper is also applicable to other extrusion processes, contributing positively to quality control in automated manufacturing.