Prediction of uniaxial and biaxial flexural strengths of resin-based composites using the Weibull model

Ghelbere, Raluca und Ilie, Nicoleta (2022): Prediction of uniaxial and biaxial flexural strengths of resin-based composites using the Weibull model. In: Journal of the Mechanical Behavior of Biomedical Materials, Bd. 131, 105231

Abstract

Objectives: The aim of the study was to assess the applicability of the Weibull model for resin-based composites (RBC) to predict the outcome of different flexural tests based on one another, while identifying the minimal sample number for a precise Weibull representation. Methods: Four RBCs underwent 3-point, 4-point and biaxial flexural testing (n = 480). Fracture surfaces of all specimens were assessed under optical microscope, while fracture modes of the uniaxial specimens were documented. Representative specimens for each fracture mode were further analyzed under scanning electron microscope. Since fracture predominantly originated from a surface flaw, the effective surface was used in the Weibull model. The analysis was performed on 20, then 30 and finally 40 specimens per group to assess the effect of the specimen size. Further statistical analysis was performed through uni-and multivariate ANOVA, Tukey's post hoc test (alpha = 0.05), and Pearson's correlation. Results: The Weibull model could predict the results of uniaxial tests within the standard deviation, with the correlation between calculated and measured values reaching values of R-2 = 0.985 and higher. Predictions for or based on the biaxial tests misestimated the measured values, with a weaker correlation (R-2 = 0.875) between measured and calculated flexural strength (FS). The fit of the data to the Weibull distribution improved with rising sample size resulting in better predictions of the FS when n = 40. Significance: The applicability of the Weibull model on RBCs allows accurate comparison between bending tests and their FS under consideration of the effective surface.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 1751-6161
• Sprache: Englisch