VAHID JAFARPOUR
Maryam Abasi
Abstract
One of the most advanced methods of metal shaping techniques is hydroforming, which uses fluid at extreme pressure to deform metal sheets that cannot be fabricated by conventional approaches. This method is perfect for the production of lightweight, seamless, continuous, mesh-shaped, high-quality, and important high-strength automotive and aircraft components. When it comes to pipe hydroforming, the ductility of the metal pipe has a direct impact on the forming load route. (Internal deformation pressure and axial feeding). This research focuses on the impact of operational circumstances. (i.e., the impact of ultimate longitudinal feeding and forming pressure) on the whole procedure and keeps the other factors fixed. The control algorithms were designed to control longitudinal feeding and pressure over the shaping process modeling. Most of the pipe hydroforming paths are created during the multi-stage procedure for loading. Hence the deformation limit strains obtained in the middle of the deformation procedure depend on the route. The present work optimizes the loading path angles in the pipe deformation procedure using an intelligent algorithm for fuzzy logic control. This prevents the tube from breaking or rupturing during the forming process due to high strains. The mentioned control algorithm and fuzzy adaptive neural system (ANSYS) were used to simulate the hydroforming procedure.
Keywords
Pipe Hydroforming,
optimal loading path,
Optimization,
Fuzzy Control.
