JOURNAL ARTICLE

Design of a novel high-speed tensile method for testing the high strain rate tensile behavior of aluminum alloys.

  • Published In: Review of Scientific Instruments, 2024, v. 95, n. 12. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Chen, Li; Shi, Hao; Li, Weihao; Shi, Huantong; Li, Xingwen; Hao, Shiyu; Li, Chengcheng; An, Ran 3 of 3

Abstract

The article focuses on a novel magnetic pulse-driven method for high-strain rate tensile testing of aluminum alloys, specifically AA7075, addressing limitations of traditional testing techniques like the Split Hopkinson Tension Bar (SHTB). This method employs a magnetic pulse driver (MPD) powered by a pulse current generator (PCG) to produce fast-rising, adjustable stress pulses that induce uniaxial tensile deformation at strain rates between 1000 and 3000 s⁻¹, with strain rates rapidly reaching and maintaining target values. Stress and strain measurements are obtained non-contact via high-speed cameras combined with digital image correlation (DIC) technology, enabling accurate stress–strain curve determination while avoiding electromagnetic interference and errors from specimen fixation or stress wave overlap common in SHTB tests. Finite element simulations using LS-DYNA corroborate experimental results, demonstrating good agreement in strain and strain rate distributions, and validating the method’s effectiveness for characterizing high-strain rate mechanical behavior relevant to electromagnetic launch systems.

Additional Information

  • Source:Review of Scientific Instruments. 2024/12, Vol. 95, Issue 12, p1
  • Document Type:Article
  • Subject Area:Engineering
  • Publication Date:2024
  • ISSN:0034-6748
  • DOI:10.1063/5.0235066
  • Accession Number:181982555
  • Copyright Statement:Copyright of Review of Scientific Instruments is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.