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Erschienen in: The International Journal of Advanced Manufacturing Technology 1-2/2021

11.05.2021 | ORIGINAL ARTICLE

A simplified formulation for predicting wrinkling of thin-wall elbow tube in granular media–based push-bending process

verfasst von: Hai Liu, Shi-Hong Zhang, Yun-Peng Ding, Gao-Lian Shi, Zhe Geng

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 1-2/2021

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Abstract

Wrinkling is the key forming defect in thin-wall tube bending process, when the wall thickness-to-diameter ratio is smaller than 0.01. The granular media-based thin-wall elbow push-bending process involves filling a tube with spherical particles and pushing the tube into a die to bend a tubular blank into an elbow shape. If the wall thickness of tube is smaller than the particle size, wrinkling significantly depends on micro contact force distribution in granular media, and the granular media cannot be approximately simulated by FEM. In the present paper, an elbow tube with 0.3 mm wall thickness, 30 mm outer diameter, and 90 mm bending radius is formed by granular media-based push-bending process. The wrinkling is investigated; especially, the micro contact force distribution at the initial buckling location is observed based on a 3D FEM-DEM coupling model. In the coupling model, FEM is used to simulate bending deformation of tubular blank, and DEM is used to simulate micro contact forces of particle flow. Finally, a simplified formulation is proposed for predicting wrinkling of thin-wall elbow tube in granular media-based push-bending process and validated by experiment of an elbow tube with 0.7 mm wall thickness, 70 mm outer diameter, and 105 mm bending radius.

Graphical abstract

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Metadaten
Titel
A simplified formulation for predicting wrinkling of thin-wall elbow tube in granular media–based push-bending process
verfasst von
Hai Liu
Shi-Hong Zhang
Yun-Peng Ding
Gao-Lian Shi
Zhe Geng
Publikationsdatum
11.05.2021
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 1-2/2021
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-021-07168-2

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