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Material characterization and damage assessment of an AA5352 aluminium alloy using digital image correlation

Title
Material characterization and damage assessment of an AA5352 aluminium alloy using digital image correlation
Type
Article in International Scientific Journal
Year
2020
Authors
Amaral, R
(Author)
Other
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Tavares, PJ
(Author)
Other
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Moreira, PMGP
(Author)
Other
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dos Santos, A
(Author)
Other
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Journal
Vol. 55
Pages: 3-19
ISSN: 0309-3247
Publisher: SAGE
Other information
Authenticus ID: P-00R-J5N
Abstract (EN): The emergence of reliable material characterization techniques in automotive and aeronautical industries, in particular sheet metal forming, promises to underpin a novel advance in materials research. In this regard, 5xxx series aluminium alloys deliver the largest formability range and can be deformed at room temperature. This study aims at determining the mechanical properties of the AA5352 aluminium alloy, using digital image correlation. Thus, tensile sheet specimens manufactured from the corresponding alloy are mechanically tested under a uniaxial condition and deformation fields are monitored. Considering the force/displacement response and stress/strain curves, the material Poisson's ratio, Young's modulus and anisotropy coefficient in the transverse direction are characterized by the experimental digital image correlation data. It intends to obtain accurate and reliable mechanical properties to be considered in the future processing analyses. Numerically, adopting the experimentally obtained material properties, the Gurson-Tvergaard-Needleman damage model is implemented using finite element method formulation to forecast the ductile fracture performance of the tested AA5352 sheet. The predicted results are then compared with the experimental digital image correlation solution verifying good agreement with the force/displacement response and the deformation fields. Overall, the acquired numerical results imply that the Gurson-Tvergaard-Needleman damage criterion is capable to render an accurate prediction upon a high stress triaxiality state.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 17
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