ASTM E1921-21a

5.1?Fracture toughness is expressed in terms of an elastic-plastic stress intensity factor, K_Jc, that is derived from the 5.2?Ferritic steels are microscopically inhomogeneous with respect to the orientation of individual grains. Also, grain boundaries have properties distinct from those of the grains. Both contain carbides or nonmetallic inclusions that can act as nucleation sites for cleavage microcracks. The random location of such nucleation sites with respect to the position of the crack front manifests itself as variability of the associated fracture toughness 5.3?The statistical methods in this test method assume that the data set represents a macroscopically homogeneous material, such that the test material has both the uniform tensile and toughness properties. The fracture toughness evaluation of nonuniform materials is not amenable to the statistical analysis procedures employed in this test method. For example, multi-pass weldments can create heat-affected and brittle zones with localized properties that are quite different from either the bulk or weld materials. Thick-section steels also often exhibit some variation in properties near the surfaces. Metallographic analysis can be used to identify possible nonuniform regions in a material. These regions can then be evaluated through mechanical testing such as hardness, microhardness, and tensile testing for comparison with the bulk material. It is also advisable to measure the toughness properties of these nonuniform regions distinctly from the bulk material. Section 10.6 provides a screening criterion to assess whether the data set may not be representative of a macroscopically homogeneous material, and therefore, may not be amenable to the statistical analysis procedures employed in this test method. If the data set fails the screening criterion in 10.6, the homogeneity of the material and its fracture toughness can be more accurately assessed using the analysis methods described in Appendix X5.

5.4?Distributions of K_Jc data from replicate tests can be used to predict distributions of K_Jc for different specimen sizes. Theoretical reasoning 5.5?The experimental results can be used to define a master curve that describes the shape and location of median K_Jc transition temperature fracture toughness for 1T specimens 5.6?Tolerance bounds on K_Jc can be calculated based on theory and generic data. For added conservatism, an offset can be added to tolerance bounds to cover the uncertainty associated with estimating the reference temperature, T₀, from a relatively small data set. From this it is possible to apply a margin adjustment to 5.7?For some materials, particularly those with low strain hardening, the value of 5.8?As discussed in 1.3, there is an expected bias among T₀ values as a function of the standard specimen type. The magnitude of the bias may increase inversely to the strain hardening ability of the test material at a given yield strength, as the average crack-tip constraint of the data set decreases 1.1?This test method covers the determination of a reference temperature, 1.2?The specimens covered are fatigue precracked single-edge notched bend bars, SE(B), and standard or disk-shaped compact tension specimens, C(T) or DC(T). A range of specimen sizes with proportional dimensions is recommended. The dimension on which the proportionality is based is specimen thickness.

1.3?Median K_Jc values tend to vary with the specimen type at a given test temperature, presumably due to constraint differences among the allowable test specimens in 1.2. The degree of 1.4?Requirements are set on specimen size and the number of replicate tests that are needed to establish acceptable characterization of K_Jc data populations.

1.5?T₀ is dependent on loading rate. 1.6?The statistical effects of specimen size on K_Jc in the transition range are treated using the weakest-link theory (4) applied to a three-parameter Weibull distribution of fracture toughness values. A limit on 1.7?Statistical methods are employed to predict the transition toughness curve and specified tolerance bounds for 1T specimens of the material tested. The standard deviation of the data distribution is a function of Weibull slope and median 1.8?The procedures described in this test method assume that the data set represents a macroscopically homogeneous material, such that the test material has uniform tensile and toughness properties. Application of this test method to an inhomogeneous material will result in an inaccurate estimate of the transition reference value 1.9?This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.

1.10?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.