Data related to the publication (we would be grateful if you could cite the paper in the case in which you are using the data):

title = "Ductile fracture of high entropy alloys: from the design of an experimental campaign to the development of a micromechanics-based modeling
framework",
journal = "Engineering Fracture Mechanics",
year = "202",
volume = "",
pages = " ",
doi = "https://doi.org/",
author = "Antoine Hilhorst, Julien Leclerc, Thomas Pardoen, Pascal J. Jacques, Ludovic Noels, Van-Dung Nguyen"
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experimentalCurves
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Contains the experimental engineering stress strain curves of the different samples and the porosity evolution of PL2 sample. 
Examples on how to read these files are provided in the directories Fig4 and Fig 10.

simulationsData
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Contains the output of simulations with identfied parameters for each sample:
 1) name.msh is the mesh file with the physical numbers that can be opened by gmsh (https://gmsh.info/)
 2) force... .csv correspond to the archived force used to compute the engineering stress
 3) NodalDisplacement... .csv correspond to the archived displacement used to compute the engineering strain
 4) IP... .csv correspond to archieved internal variables at specific locations (see mesh file)
 
 Examples on how to read these files are provided in the directories Fig18Fig19

Fig4
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Contains the python file to read the data in the directory experimentalCurves and to generate Fig. 4.

Fig5
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Contains fracture strains of all tests and the python file to generate Fig 5.

Fig10
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Contains the python file to load and vizualize the porosity evolution of files of experimentalCurves/exp-2PL

Fig19
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Contains the python file to read the data in the directories experimentalCurves and simulationsData and to generate Fig 19.

Fig20
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Contains the python file to read the data in the directories experimentalCurves and simulationsData and to generate Fig 20.
csv file can be generated using generateData.py of root directory

Fig22
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DIC data

Fig23
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Contains the python file to read the data in the directories experimentalCurves and simulationsData and to generate Fig 23.
csv file can be generated using generateData.py of root directory

Fig24
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Contains the python file to read the data in the directories experimentalCurves and simulationsData and to generate Fig 24.
csv file can be generated using generateData.py of root directory

