A data analysis procedure for phase identification in nanoindentation results of cementitious materials
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Measuring accurately phase properties is essential for a realistic mesoscale modeling of materials, and nanoindentation is a popular technique regarding mechanical properties. Given the statistical nature of the grid indentation method, where large arrays of indents are performed blindly, the identification of phases from the distributions of measured properties is an essential step. Many biases can be introduced at that stage when the phases do not have very distinct properties as is often the case for cementitious materials, since many indentation tests may also be in effectively heterogeneous areas. It is proposed in the present work to analyze statistical indentation results on cementitious materials with a hierarchical clustering algorithm making use of enriched information, including the spatial coordinates of the indent. It is shown that it allows to reduce potential biases of the method by eliminating tests in potentially heterogeneous areas and performing model independent identification of the different phases.
KeywordsNanoindentation Micromechanics Cementitious materials Unsupervised clustering
This work has been carried out in the framework of the CEA-EDF-Framatome agreement. The author thanks S. Poyet (CEA) for discussions regarding the manuscript.
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