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Standard Practice for Reporting Uniaxial Strength Data and Estimating Weibull Distribution Parameters for Advanced Ceramics
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Standard [NEW]

ASTM C 1239:2026

Standard Practice for Reporting Uniaxial Strength Data and Estimating Weibull Distribution Parameters for Advanced Ceramics

Publication date
2026
Original language
English
Pages
20

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Publication date
2026
Original language
English
Pages
20
DOI
https://dx.doi.org/10.1520/C1239-26

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Short description

1.1 This practice covers the evaluation and reporting of uniaxial strength data and the estimation of Weibull probability distribution parameters for advanced ceramics that fail in a brittle fashion (see Fig. 1 ). The estimated Weibull distribution parameters are used for statistical comparison of the relative quality of two or more test data sets and for the prediction of the probability of failure (or, alternatively, the fracture strength) for a structure of interest. In addition, this practice encourages the integration of mechanical property data and fractographic analysis. 1.2 The failure strength of advanced ceramics is treated as a continuous random variable determined by the flaw population. Typically, a number of test specimens with well-defined geometry are failed under isothermal, well-defined displacement and/or force-application conditions. The force at which each test specimen fails is recorded. The resulting failure stress data are used to obtain Weibull parameter estimates associated with the underlying flaw population distribution. 1.3 This practice is restricted to the assumption that the distribution underlying the failure strengths is the two-parameter Weibull distribution with size scaling. Furthermore, this practice is restricted to test specimens (tensile, flexural, pressurized ring, etc.) that are primarily subjected to uniaxial stress states. The practice also assumes that the flaw population is stable with time and that no slow crack growth is occurring. 1.4 The practice outlines methods to correct for bias errors in the estimated Weibull parameters and to calculate confidence bounds on those estimates from data sets where all failures originate from a single flaw population (that is, a single failure mode). In samples where failures originate from multiple independent flaw populations (for example, competing failure modes), the methods outlined in Section 9 for bias correction and confidence bounds are not applicable. 1.5 This practice includes the following: Section Scope 1 Referenced Documents 2 Terminology 3 Summary of Practice 4 Significance and Use 5 Interferences 6 Outlying Observations 7 Maximum Likelihood Parameter Estimators for Competing Flaw Distributions 8 Unbiasing Factors and Confidence Bounds 9 Fractography 10 Examples 11 Keywords 12 Computer Algorithm MAXL Appendix X1 Test Specimens with Unidentified Fracture Origins Appendix X2 1.6 The values stated in SI units are to be regarded as the standard per IEEE/ASTMSI10 . 1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

ICS

81.060.99

DOI

https://dx.doi.org/10.1520/C1239-26
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