This part of EN 843 specifies a method for statistical analysis of ceramic strength data in terms of a two-parameter Weibull distribution using a maximum likelihood estimation technique. It assumes that the data set has been obtained from a series of tests under nominally identical conditions.
NOTE 1 In principle, Weibull analysis is considered to be strictly valid for the case of linear elastic fracture behaviour to
the point of failure, i.e. for a perfectly brittle material, and under conditions in which strength limiting flaws do not interact
and in which there is only a single strength-limiting flaw population.
If subcritical crack growth or creep deformation preceding fracture occurs, Weibull analysis can still be applied if the results fit a Weibull distribution, but numerical parameters may change depending on the magnitude of these effects.
Since it is impossible to be certain of the degree to which subcritical crack growth or creep deformation has occurred, this
European Standard permits the analysis of the general situation where crack growth or creep may have occurred, provided that it is recognized that the parameters derived from the analysis may not be the same as those derived from data with no subcritical crack growth or creep.
NOTE 2 This European Standard employs the same calculation procedures as method A of ISO 20501:2003 [1], but does not provide a method for dealing with censored data (method B of ISO 20501).
BS EN 843-5:2006 Referenced Document
EN 843-1:2006 Advanced technical ceramics - Mechanical properties of monolithic ceramics at room temperature - Part 1: Determination of flexural strength*, 2024-04-18 Update
EN ISO/IEC 17025 General requirements for the competence of testing and calibration laboratories*, 2017-12-01 Update
BS EN 843-5:2006 history
2007BS EN 843-5:2007 Advanced technical ceramics - Mechanical properties of monolithic ceramics at room temperature - Statistical analysis
2007BS EN 843-5:2006 Advanced technical ceramics — Mechanical properties of monolithic ceramics at room temperature — Part 5: Statistical analysis