Journal
MATERIALS & DESIGN
Volume 222, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.matdes.2022.111080
Keywords
Friction Stir Welding (FSW); Dissimilar Al alloys; Laser induced shock wave propagation; VISAR analysis; Dynamic simulation
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Funding
- Direction Generale de l'Armement (DGA) Rapid
- French Agence Nationale de la Recherche (ANR) [ANR18-CE08-0026]
- Slovenian Research Agency [P2-0270, BI-FR/20-21-010, BI-RS/2021-047]
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This study introduces an innovative methodology for material characterization under high strain rate laser shock loading, with experimental and simulation analyses conducted for Al alloys and Friction Stir Welded joints, showing high potential for predicting material properties and behavior.
This paper presents an innovative methodology of material characterization under high strain rate (order of 10(7)s(-1)) laser shock loading coupled with microstructural and mechanical material features. To that scope, experimental and simulation analyses have been conducted for Al alloys (AA7075-T6 and AA2017-T4) and dissimilar Friction Stir Welded (FSWed) AA7075-AA2017 joint, under shock pressure of 4.5 GPa (laser power density of 3.5 GW=cm(2)). In order to perform proper in-depth material model simulation of these alloys and dissimilar pairs, Johnson-Cook (J-C) material model has been coupled with Gruneisen equation of state using the non-linear explicit code LS-DYNA. For the first time, we provided a way to differentiate between material behaviour in the cross-section and the in-plane rolling and welding direction. What is more, we have provided the link between microstructural features and mechanical properties such as microhardness, residual stresses and the identified material parameters. By achieving this goal, the bigger difference between studied planes was confirmed for strain hardening modulus, strain hardening exponent and strain rate sensitivity parameters. Obtained results and proposed methodology indicate high potential to predict material properties and behaviour of dynamically stressed parts and at the same time can be used for optimization of LSP process. (C) 2022 The Authors. Published by Elsevier Ltd.
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