4.6 Article

Forming characteristics analysis and springback prediction of bi-directional trapezoidal sandwich panels in the multi-point bend-forming

Journal

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00170-018-2316-z

Keywords

Bi-directional trapezoidal sandwich panels; Multi-point bending; Forming characteristics; Springback

Funding

  1. National Science Foundation of China [51575231]

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Bend-forming is an efficient and economical method to manufacture curved sandwich panels, and the major concerns for fabricating precise products are forming characteristics and springback prediction. In this paper, numerical simulation, analytical approach, and forming experiments were conducted to assess the multi-point cylindrical bend-forming process of bi-directional trapezoidal sandwich panel. Analysis was performed on the deformation characteristics. regularity, and forming defects of sandwich panel in the early stage. And afterwards, equivalent elastic constants of the core layer were deduced by the semi-analytic approach combined with finite element method (FEM). On this basis, a theoretical model was established to calculate bending moments and predict springback within formable range. The results indicate that the stress of face sheet in the welded area was obviously lower than that in the suspended area. The core cell was primarily deformed by changing the angle between the inclined plane and the platform, and the deformation of the cell layer mainly occurred in the transition surface area. The dimple and straight plane effect are the most common forming defects during the bending process. The main factors that affect the forming defects are face sheet thickness and bending radius. The springback amount of the sandwich panel approximates the equivalent thickness plate. Thus, it is easy to control the forming precision for small springback, and the springback ratio increases with the increase of bending curvature radius. The springback in theoretical model and experiment has an error of less than 1.0 mm, verifying the accuracy of the theoretical prediction model.

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