A methodology based on the Birnbaum–Saunders distribution for reliability analysis applied to nano-materials

VICTOR ELISEO LEIVA SANCHEZ, Fabrizio Ruggeri, Helton Saulo, Juan F. Vivanco

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

The Birnbaum–Saunders distribution has been widely studied and applied to reliability studies. This paper proposes a novel use of this distribution to analyze the effect on hardness, a material mechanical property, when incorporating nano-particles inside a polymeric bone cement. A plain variety and two modified types of mesoporous silica nano-particles are considered. In biomaterials, one can study the effect of nano-particles on mechanical response reliability. Experimental data collected by the authors from a micro-indentation test about hardness of a commercially available polymeric bone cement are analyzed. Hardness is modeled with the Birnbaum–Saunders distribution and Bayesian inference is performed to derive a methodology, which allows us to evaluate the effect of using nano-particles at different loadings by the R software.

Original languageEnglish
Pages (from-to)192-201
Number of pages10
JournalReliability Engineering and System Safety
Volume157
DOIs
StatePublished - 1 Jan 2017

Keywords

  • Bayesian analysis
  • Hardness data
  • Markov chain Monte Carlo method
  • R software

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