Springback Behavior and Stroke-Based Compensation Strategy for Roll-Based Bending of High-Strength Aluminum Extrusions

High-strength aluminum tubular extrusions are being increasingly used in lightweight automotive structures; however, the significant springback caused by elastic recovery after bending compromises geometric accuracy. In roll-based bending processes, springback behavior is affected by multiple process parameters, which necessitates a systematic investigation and a simulation-based springback compensation approach. In this study, the springback behavior of high-strength aluminum tubular extrusions subjected to roll-based bending was investigated via finite-element analysis. The effects of feeding displacement, roller rotational speed, and internal mandrel application on springback were comparatively evaluated. Springback was quantitatively assessed based on the displacement and angular deviation after unloading, and the influence of each process parameter was analyzed. Based on the results, variations in roller rotational speed had a negligible effect on springback, whereas feeding displacement was identified as the dominant governing factor under all investigated conditions. Although internal mandrel application reduced stress levels and mitigated wrinkle formation, the overall springback tendency remained dependent on feeding displacement. Based on these findings, a simulation-based stroke compensation approach was proposed, and a compensation window satisfying the target curvature radius of R = 150 mm was numerically identified under the investigated finite-element conditions.

Authors

Institutions

Publication Details

Journal
Materials
Published
2026-08-03
DOI
https://doi.org/10.3390/ma19153275
Primary Topic
Metal Forming Simulation Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Springback Behavior and Stroke-Based Compensation Strategy for Roll-Based Bending of High-Strength Aluminum Extrusions

Jin Ho Kim, Jeongsik Lim, Changhwan Seo, Hyungjun Kim et al.
Materials
Metal Forming Simulation Techniques
article

Springback Behavior and Stroke-Based Compensation Strategy for Roll-Based Bending of High-Strength Aluminum Extrusions

Jin Ho Kim, Jeongsik Lim, Changhwan Seo, Hyungjun Kim, Hoyoung Kang, Haeyong Yun
article en

Abstract

High-strength aluminum tubular extrusions are being increasingly used in lightweight automotive structures; however, the significant springback caused by elastic recovery after bending compromises geometric accuracy. In roll-based bending processes, springback behavior is affected by multiple process parameters, which necessitates a systematic investigation and a simulation-based springback compensation approach. In this study, the springback behavior of high-strength aluminum tubular extrusions subjected to roll-based bending was investigated via finite-element analysis. The effects of feeding displacement, roller rotational speed, and internal mandrel application on springback were comparatively evaluated. Springback was quantitatively assessed based on the displacement and angular deviation after unloading, and the influence of each process parameter was analyzed. Based on the results, variations in roller rotational speed had a negligible effect on springback, whereas feeding displacement was identified as the dominant governing factor under all investigated conditions. Although internal mandrel application reduced stress levels and mitigated wrinkle formation, the overall springback tendency remained dependent on feeding displacement. Based on these findings, a simulation-based stroke compensation approach was proposed, and a compensation window satisfying the target curvature radius of R = 150 mm was numerically identified under the investigated finite-element conditions.

MaterialsVol. 19(15)
Korea Institute of Robot and Convergence (KR), Korea Basic Science Institute (KR), Pohang TechnoPark (South Korea) (KR), Yeungnam University (KR)
Openalex Percentile: Top 17%
Metal Forming Simulation Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.