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Characterization of ductile damage for a high carbon steel using 3D X-ray micro-tomography and mechanical tests - Application to the identification of a shear modified GTN model

Abstract : The present paper deals with the identification of the parameters of a generalized GTN model and the characterization of ductile damage for a high carbon steel by both X-ray micro-tomography and "macroscopic" mechanical tests. First, in situ X-ray micro-tomography tensile tests are performed and the results are used for the modeling of ductile damage mechanisms (voids nucleation, growth and coalescence) using analytical formulations. Interrupted in situ SEM tensile test is also carried out to examine the microstructure evolution. The damage process during in situ X-ray micro-tomography tensile tests is the result of continuous nucleation of small voids and significant growth of large voids; whereas the coalescence takes place locally. In addition, tomography results combined with the results of macroscopic mechanical tests at different loading configurations are used to identify the Gurson-Tvergaard-Needleman model extended for shear loading by Xue (2008). It proved necessary to propose an improvement to account for the influence of the stress triaxiality level on the nucleation formulation of the GTN model. This new formulation is then identified via experimental tests. The results show that, with the parameters obtained from both microstructure measurements and macroscopic considerations, the modified GTN model can reproduce quite accurately the experimental results for different loading configurations.
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https://hal-mines-paristech.archives-ouvertes.fr/hal-00944805
Contributor : Trong Son Cao <>
Submitted on : Tuesday, February 11, 2014 - 11:23:28 AM
Last modification on : Tuesday, September 14, 2021 - 11:20:01 PM

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Trong-Son Cao, Éric Maire, Catherine Verdu, Christian Bobadilla, Patrice Lasne, et al.. Characterization of ductile damage for a high carbon steel using 3D X-ray micro-tomography and mechanical tests - Application to the identification of a shear modified GTN model. Computational Materials Science, Elsevier, 2014, 84, pp.175 - 187. ⟨10.1016/j.commatsci.2013.12.006⟩. ⟨hal-00944805⟩

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