Residual Stress Distribution in a Hydroformed Advanced High Strength Steel Component: Neutron Diffraction Measurements and Finite Element Simulations United States Steel Corporation

Format:

Conference/Event

Author/Creator:

Huang, Huang, author.

Contributor:

An, Ke

Chen, Xiaoming

Chen, Yan

Yu, Dunji

Conference Name:

WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2018

Summary:

Today's automotive industry is witnessing increasing applications of advanced high strength steels (AHSS) combined with innovative manufacturing techniques to satisfy fuel economy requirements of stringent environmental regulations. The integration of AHSS in novel automotive structure design has introduced huge advantages in mass reduction while maintaining their structural performances, yet several concerns have been raised for this relatively new family of steels. One of those concerns is their potentially high springback after forming, which can lead to geometrical deviation of the final product from its designed geometry and cause difficulties during assembly. From the perspective of accurate prediction, control and compensation of springback, further understanding on the effect of residual stress in AHSS parts is urged. In this work, the residual stress distribution in a 980GEN3 steel part after hydroforming is investigated via experimental and numerical approaches. A non-destructive neutron diffraction technique is adopted to reveal the residual stress profiles across a 94-degree tube bending radius section of the hydroformed part. The finite element analysis (FEA) is also conducted to simulate the hydroforming and the subsequent unloading processes to predict the residual stress distribution within the same region. The correlation between experimental and simulation results is presented and the effectiveness of the FEA model for residual stress prediction is discussed. Findings in this study set the basis for springback analysis with improved accuracy and reliability

Notes:

Vendor supplied data

Publisher Number:

2018-01-0803

Access Restriction:

Restricted for use by site license