Anisotropic behavior and mechanism in electropulsing-assisted deep drawing of Ti/al laminated composite cups
Source abstract
Abstract
Ti/Al laminated composite plates (Ti/Al LCPs) are lightweight materials with high specific strength and excellent corrosion resistance, making them ideal for applications in high-tech sectors such as aerospace and rail transportation. However, these plates often exhibit anisotropic characteristics due to rolling deformation. During deep drawing, edge waviness, known as the earing effect, can cause non-uniform wall thickness in formed cups, leading to cracks at the peaks and valleys, thereby affecting product quality. The electropulsing-assisted deep drawing (EPAD) process leverages the Joule heating effect and electron wind to offer a novel approach for controlling material anisotropy. This study conducts EPAD experiments on Ti/Al LCPs under varying current parameters and develops a deep drawing simulation model. Upon the application of current, the forming force decreases, the force mutation in phase II vanishes, and the thinning rate at the punch corner drops to 13.53%. The average cup height ( ) increases by approximately 1.31 mm, the earing height index ( ) reduces by approximately 0.18 mm, and earing amplitude ratio ( ) decreases by about 1.72. The deep drawing simulation model, which incorporates anisotropy parameters, successfully predicts the wall thickness and cup height values with an AARE of approximately 3.659%. These findings indicate that introducing pulsed current into the forming process effectively reduces the required deep drawing force, improves the forming quality, and suppresses earing to some extent. The results provide valuable insights for optimizing the manufacturing processes of Ti/Al LCP components and enhancing the service performance of formed parts.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Electromagnetic Effects on Materials · Metal Forming Simulation Techniques · Surface Treatment and Residual Stress
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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