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Understanding the mechanical properties of novel UHTCMCs through random forest and regression tree analysis

Authors: Vinci Antonio; Zoli L.; Sciti D.; Melandri C.; Guicciardi o Guizzardi S.;

Understanding the mechanical properties of novel UHTCMCs through random forest and regression tree analysis

Abstract

The microstructure and the mechanical properties of ZrB2-SiC-Cf ceramic composites were investigated. The SiC phase, whose amount was varied from 5 to 20 vol%, was introduced in order to improve the densification, oxidation resistance and mechanical properties of the composite. The microstructure was analysed by SEM-EDS and image analysis. Increasing the amount of SiC from 5 to 20 vol% resulted in an improvement of the materials density, from 90% to 94%. The non-brittle 4-pt flexural strength ranged from 164 to 247 MPa, with no clear dependence on the amount of SiC added. The same holds true for the fracture toughness, ranging from 4.8 to 8.4 MPa·m0.5. In order to track the most important microstructural parameters affecting the properties, experimental data were analysed with the Random Forest and Regression Tree statistical models. The statistical analysis demonstrated that among the possible explanatory variables such as porosity, amount of SiC, fibre content, matrix content, SiC/fibre amount ratio, the one having a major influence on both the flexural strength and fracture toughness is the ratio between SiC and carbon fibre content.

Country
Italy
Keywords

Fibre-matrix interface, Statistical methods, Ceramic-Matrix Composites (CMCs), Mechanical properties, Ultra-High-Temperature-Ceramics (UHTCs), Zirconium diboride

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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53
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