journal article·2014-04

Influence of sample size on strength distribution of advanced ceramics

Serkan Nohut

Ceramics International· Volume 40· Issue 3
Publisher page

Abstract

Abstract Strength distribution of advanced ceramics is mostly characterized by Weibull distribution function. The question whether the Weibull distribution always gives the best fit to strength data has been being considered in the last years. The sample size affects the reliable decision of discrimination of different distribution functions (e.g. normal, log-normal, gamma or Weibull). In this paper, 5100 experimental alumina strength data and virtual strength data generated by Monte Carlo simulations are used in order to investigate the effect of sample size on strength distribution of advanced ceramics. It is suggested that, at least 150–200 samples should be used for determination of best fitting distribution function with a statistical fallibility of 10%. Extreme Value Analysis performed with the experimental strength data showed that the Weibull distribution fits the data best and difference between the Weibull and Gumbel distributions appear at the tails.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Numerical methods in engineering · Advanced ceramic materials synthesis · Rock Mechanics and Modeling

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (52)

Show source-provided references
1. Structural reliability: a processing-dependent phenomenon10.1111/j.1151-2916.1982.tb10380.x ↗
2. Fracture of ceramics10.1002/adem.200700347 ↗
3. Lawn · 1993
4. Reliability-based design of ceramics10.1016/0261-3069(94)90055-8 ↗
5. The phenomena of rupture and flow in solids10.1098/rsta.1921.0006 ↗
6. Munz · 1999
7. Predicting lifetimes of materials and material structures10.1016/0109-5641(95)80050-6 ↗
8. Failure probability of ceramic coil springs10.1016/j.jeurceramsoc.2008.08.012 ↗
9. Determination of the multiaxial failure criteria for alumina ceramics under tension–torsion test10.1016/j.jeurceramsoc.2010.08.008 ↗
10. A general strength distribution function for brittle materials10.1016/0955-2219(92)90021-5 ↗
11. Fracture statistics of ceramics—Weibull statistics and deviations from Weibull statistics10.1016/j.engfracmech.2006.05.028 ↗
12. Fracture statistics of brittle materials: Weibull or normal distribution10.1103/PhysRevE.65.067102 ↗
13. A statistical distribution function of wide applicability10.1115/1.4010337 ↗
14. Mechanics-based statistics of failure risk of quasibrittle structures and size effect on safety factors10.1073/pnas.0602684103 ↗
15. Weakest-link failure predictions for ceramics IV: application of mixed-mode fracture criteria for multiaxial loading10.1016/0955-2219(92)90125-W ↗
16. Influence of threshold stress on the estimation of the Weibull statistics10.1111/j.1151-2916.2002.tb00330.x ↗
17. Some notes on the correlation between fracture and defect statistics: are Weibull statistics valid for very small specimens?10.1016/j.jeurceramsoc.2005.08.021 ↗
18. Simulation of strength distribution in ground ceramics by incorporating residual stress effect10.1007/s11665-007-9169-1 ↗
19. Is Weibull distribution the most appropriate statistical strength distribution for brittle materials?10.1016/j.ceramint.2007.10.003 ↗
20. Fracture statistics of dental ceramics: discrimination of strength distributions10.1016/j.ceramint.2012.02.093 ↗
21. ENV843-5: in Advanced Technical Ceramics, Monolithic Ceramics; Mechanical Tests at Room Temperature, Part 5-Statistical Analysis, (1997) p. 41.
22. Monte Carlo simulations of strength distributions of brittle materials: type of distribution, specimen and sample size
23. Bend strength of alumina ceramics: a comparison based on very large experimental data set10.1016/j.jeurceramsoc.2011.12.010 ↗
24. Castillo · 1988
25. Fracture statistics: a comparison of the normal, Weibull and type I extreme value distributions10.1063/1.331731 ↗
26. The fracture load and failure types of veneered anterior zirconia crowns: an analysis of normal and Weibull distribution of complete and censored data10.1016/j.dental.2011.11.023 ↗
27. Kotz · 2000
28. Limiting forms of the frequency distribution of the largest or smallest member of a sample10.1017/S0305004100015681 ↗
29. Ledermann · 1980
30. Z.P. Bazant, D. Novak, Stochastic models for deformation and failure of quasistatic structures: Recent advances and new directions, Computational Modeling of Concrete Structures, in: N. Bicanic, R. de Borst, H. Mang, G. Meschke, (Eds.), Proceedings of the Euro-C Conference, St. Johann im Pongau, Austria, A.A. Balkema Publ., Lisse, Netherlands, (2003) pp. 583–598.
31. Z.P. Bazant, D. Novak, Nonlocal model for size effect in quasibrittle failure based on extreme value statistics, Structural Safety and Reliability, Corotis et al. (Ed.), 2001
32. Review: a practical and systematic review of Weibull statistics for reporting strengths of dental materials10.1016/j.dental.2009.09.006 ↗
33. Bury · 1975
34. Kapur · 1977
35. Five deductions of Weibull's distribution function in the probabilistic strength of materials10.1016/0013-7944(90)90402-3 ↗
36. On estimating the Weibull modulus for a brittle material10.1007/BF00561290 ↗
37. A numerical study on the application of the Weibull theory to brittle materials10.1016/S0013-7944(01)00022-4 ↗
38. Maximum likelihood estimation for the three-parameter Weibull cdf of strength in presence of concurrent flaw populations10.1016/j.jeurceramsoc.2013.02.028 ↗
39. An iterative method to obtain the specimen-independent three-parameter Weibull distribution of strength from bending tests10.1016/j.proeng.2011.04.235 ↗
40. Stress state dependence of the shape parameter of the three-parameter Weibull distribution in relation to fracture of ceramics10.1016/0013-7944(91)90223-N ↗
41. The effect of the threshold stress on the determination of the Weibull parameters in probabilistic failure analysis10.1016/S0013-7944(03)00070-5 ↗
42. Analysis of strength data using two-and three-parameter Weibull models10.1023/A:1004361222711 ↗
43. Estimator Type and Population Size for Estimating the Weibull Modulus in Ceramics10.1016/S0955-2219(97)00165-9 ↗
44. A new look at the statistical model identification10.1109/TAC.1974.1100705 ↗
45. Optimum information in cracking noise10.1103/PhysRevE.72.027101 ↗
46. Asymptotic theory of certain goodness-of-fit criteria based on stochastic processes10.1214/aoms/1177729437 ↗
47. EDF statistics for goodness of fit and some comparisons10.1080/01621459.1974.10480196 ↗
48. Asymptotic results for goodness-of-fit statistics with unknown parameters10.1214/aos/1176343411 ↗
49. Goodness of fit for the extreme value distribution10.1093/biomet/64.3.583 ↗
50. Tests of fit for the logistic distribution based on the empirical distribution function10.1093/biomet/66.3.591 ↗
51. Strength evolution of injection-molded ceramic parts during wick-debinding10.1111/j.1551-2916.2011.04872.x ↗
52. Statistical damage mechanics and extreme value theory10.1177/1056789507060779 ↗