Cross-sectional distortion of LSAW pipes in over-bend straightening process. (August 2018)

• Record Type: Journal Article
• Authors: Wang, Chunge; Zhang, Zhiyuan; Zhai, Ruixue; Yu, Gaochao; Zhao, Jun
• Is Part Of: Thin-walled structures. Volume 129(2018)
• Page Start: 85
• Page End: 93
• Publication Date: 2018-08
• Subjects: LSAW pipes -- Cross-sectional distortion -- Over-bend straightening -- Initial curvature -- Minimum work principle; Thin-walled structures -- Periodicals; 690.1
• DOI: 10.1016/j.tws.2018.03.016
• Languages: English
• ISSNs: 0263-8231

Abstract

Abstract: In the over-bend straightening process of longitudinally submerged arc welding (LSAW) pipes, the cross section tends to be distorted due to the axial curvature variation in the reverse elastic-plastic bending. Based on the minimum work principle, a analytical model of the cross-sectional distortion of the curved pipe with initial curvature in the reverse axial elastoplastic bending is established, and the prediction error is not more than 10% compared with the experimental value of the maximum distortion coefficient. Especially for smaller deformations and thinner pipes, the prediction accuracy is higher. Compared to ovality, the maximum distortion coefficient with a smaller error can be used as an effective prediction parameter. In addition, the application of this prediction model is analyzed by an example of a straightness-offgrade LSAW pipe. The results show that the maximum value and position of cross section with most serious distortion can be determined once the initial curvature of a curved pipe is measured, which can be compared with the standard to adjust the shape of the straightening tools and process parameters. Highlights: The analytical model of the cross-sectional distortion of the curved pipe in the reverse bending is established. In the straightening process of the LSAW pipe, the maximum value and position of distorted-section can be predicted. For thicker pipes or more severe bending, the analytical model can provide larger and safer process parameters.