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Alexander Brosius

Researcher at Dresden University of Technology

Publications -  144
Citations -  2171

Alexander Brosius is an academic researcher from Dresden University of Technology. The author has contributed to research in topics: Forming processes & Sheet metal. The author has an hindex of 19, co-authored 128 publications receiving 1681 citations. Previous affiliations of Alexander Brosius include Technical University of Dortmund.

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Bulk forming of sheet metal

TL;DR: In this article, the authors define a new class of sheet-bulk metal forming processes, give an overview of the existing processes belonging to this class, highlight the tooling aspects as well as the resulting product properties and present a short summary of the relevant work that has been done towards modeling and simulation.
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Testing and modelling of material behaviour and formability in sheet metal forming

TL;DR: In this paper, the authors provide a critical review of the models available today for predicting the material behaviour at both industrial and scientific level, and the tests needed to identify the models' material parameters.
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An experimental and numerical investigation of different shear test configurations for sheet metal characterization

TL;DR: In this paper, a detailed analysis of the experimental strain distribution measured by digital image correlation is discussed for each test and the applicability of each test for the observation of the material behavior under shear stress with a view to material modeling for finite element simulations.
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Characterization of anisotropy of sheet metals employing inhomogeneous strain fields for Yld2000-2D yield function

TL;DR: In this paper, a method to include the distribution of strains in the identification of the planar anisotropy of sheet metals is proposed, which includes the optical measurement of strains on a flat specimen with a varying cross-section and an inverse parameter identification scheme which minimizes the differences between the numerical simulation results and the experimental measurements by using Levenberg-Marquardt algorithm.