Assessment of Analytical Models of Pure Bending of Sheet Materials Using the Digital Image Correlation Method. (10th May 2016)

• Record Type: Journal Article
• Authors: Govindasamy, G.; Jain, M. K.
• Is Part Of: Strain. Volume 52:Number 3(2016:Jun.)
• Page Start: 191
• Page End: 204
• Publication Date: 2016-05-10
• Subjects: digital image correlation -- numerical model -- optical strain measurement -- plane strain plastic bending; Strains and stresses -- Measurement -- Periodicals; 624.176
• DOI: 10.1111/str.12181
• Languages: English
• ISSNs: 0039-2103

Abstract

Abstract: Bending of sheet materials is a common forming mode for shaping sheet components. Although many numerical models of bending, both analytical and numerical simulations based, are available in the literature, extensive experimental validations have been rather limited. A new bend test method and complementary three‐dimensional finite element (FE) simulation of the experiments are employed to assess the predictions from an advanced analytical and FE model of pure bending of aluminium sheet materials. The experimental set‐up developed and utilised is an open concept design that allows access to the tensile surface and through‐thickness region in the vicinity of the specimen bend line to continuously record images of the deforming specimen with two cameras. The specimen images are analysed for strains using an online strain mapping system based on digital image correction method. Tangential strain distribution results from the models in terms of material thinning in the bend region are compared with those from the experiments on AA2024 aluminium sheet material by considering the responses from the specimen edges and mid‐width regions at the bend line. Furthermore, the tangential and radial stress distributions on the through‐thickness section of the specimen from the analytical model are compared with those from the FE model. The results from experiments, FE model and analytical model are compared and discussed in the light of the experimental data and the assumptions involved in the development of the models.