ASTM E1921-17a

1.1 This test method covers the determination of a reference temperature, T_o, which characterizes the fracture toughness of ferritic steels that experience onset of cleavage cracking at elastic, or elastic-plastic K_Jc instabilities, or both. The specific types of ferritic steels (3.2.1) covered are those with yield strengths ranging from 275 to 825 MPa (40 to 120 ksi) and weld metals, after stress-relief annealing, that have 10 % or less strength mismatch relative to that of the base metal.

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 K_Jc variability among specimen types is analytically predicted to be a function of the material flow properties (1)2 and decreases with increasing strain hardening capacity for a given yield strength material. This K_Jc dependency ultimately leads to discrepancies in calculated T_o values as a function of specimen type for the same material. T_o values obtained from C(T) specimens are expected to be higher than T_o values obtained from SE(B) specimens. Best estimate comparisons of several materials indicate that the average difference between C(T) and SE(B)-derived T_o values is approximately 10°C (2). C(T) and SE(B) T_o differences up to 15°C have also been recorded (3). However, comparisons of individual, small datasets may not necessarily reveal this average trend. Datasets which contain both C(T) and SE(B) specimens may generate T_o results which fall between the T_o values calculated using solely C(T) or SE(B) specimens. It is therefore strongly recommended that the specimen type be reported along with the derived T_o value in all reporting, analysis, and discussion of results. This recommended reporting is in addition to the requirements in 11.1.1.

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 T_o is dependent on loading rate. T_o is evaluated for a quasi-static loading rate range with 0.1< dK/dt < 2 MPa√m/s. Slowly loaded specimens (dK/dt < 0.1 MPa√m) can be analyzed if environmental effects are known to be negligible. Provision is also made for higher loading rates (dK/dt > 2 MPa√m/s) in Annex A1.

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 K_Jc values, relative to the specimen size, is specified to ensure high constraint conditions along the crack front at fracture. For some materials, particularly those with low strain hardening, this limit may not be sufficient to ensure that a single-parameter (K_Jc) adequately describes the crack-front deformation state (5).

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 K_Jc. The procedure for applying this information to the establishment of transition temperature shift determinations and the establishment of tolerance limits is prescribed.

1.8 This test method assumes that the test material is macroscopically homogeneous such that the materials have uniform tensile and toughness properties. The fracture toughness evaluation of nonuniform materials is not amenable to the statistical analysis methods employed in the main body of this test method. Application of the analysis of this test method to an inhomogeneous material will result in an inaccurate estimate of the transition reference value T_o and non-conservative confidence bounds. For example, mu