1.1 该测试方法涵盖了参考温度的测定， T 0 ，它表征了铁素体钢在弹性或弹塑性状态下发生解理开裂的断裂韧性 K Jc 不稳定或两者兼而有之。铁素体钢的具体类型( 3.2.2 )所涵盖的是屈服强度在275 MPa至825 MPa（40 ksi至120 ksi）范围内的那些，以及在应力消除退火后与母材强度不匹配10%或更低的焊接金属。 1.2 所涵盖的试样为疲劳预裂单边切口弯曲钢筋SE（B）和标准或盘形紧凑拉伸试样C（T）或DC（T）。建议使用一系列比例尺寸的试样。 比例所依据的尺寸是试样厚度。 1.3 中值的 K Jc 在给定的试验温度下，值往往因试样类型而异，这可能是由于允许的试样之间的约束差异 1.2 .程度 K Jc 分析预测，试样类型之间的可变性是材料流动特性的函数 ( 1. ) 2. 并且对于给定的屈服强度材料，随着应变硬化能力的增加而降低。这个 K Jc 依赖性最终会导致计算结果的差异 T 0 同一材料的试样类型的函数值。 T 0 从C（T）试样中获得的值预计高于 T 0 从SE（B）试样中获得的值。对几种材料的最佳估计比较表明，C（T）和SE（B）之间的平均差异- 衍生 T 0 值约为10°C ( 2. ) .C（T）和SE（B） T 0 还记录了高达15°C的差异 ( 3. ) 然而，对单个小数据集的比较不一定能揭示这种平均趋势。包含C（T）和SE（B）样本的数据集可以生成 T 0 结果介于 T 0 仅使用C（T）或SE（B）试样计算的值。因此，强烈建议将样本类型与衍生样本一起报告 T 0 所有报告、分析和讨论结果的价值。本推荐报告是对以下要求的补充 11.1.1 . 1.4 对建立可接受的特征所需的样本大小和重复测试次数提出了要求 K Jc 数据群体。 1.5 T 0 取决于 K -率。 T 0 被评估为准静态 K -速率范围为0.5< <2 MPa√m/s。 T 0 缓慢加载试样的值( 如果已知环境影响可以忽略不计，则<0.5 MPa√m）可视为有效。还为更高的费用编列了经费 K -费率( >2 MPa√m/s）英寸 附件A1 请注意，此阈值 K -应用率 附件A1 是一个比其他断裂韧性测试方法（如 E399 和 E1820 . 1.6 样本大小对 K Jc 在过渡范围内，使用最弱环节理论进行处理 ( 4. ) 应用于断裂韧性值的三参数威布尔分布。限制 K Jc 指定相对于试样尺寸的值，以确保断裂时沿裂纹前缘的高约束条件。对于某些材料，特别是那些低应变硬化的材料，这一限制可能不足以确保单一参数( K Jc )充分描述裂纹前缘变形状态 ( 5. ) . 1.7 采用统计方法预测所测试材料1T试样的过渡韧性曲线和规定的公差范围。数据分布的标准偏差是威布尔斜率和中值的函数 K Jc 规定了将此信息应用于建立转变温度偏移测定和建立公差限值的程序。 1.8 本试验方法中描述的程序假设数据集代表宏观均匀的材料，使得试验材料具有均匀的拉伸和韧性。将此测试方法应用于非均匀材料将导致过渡参考值的估计不准确 T 0 以及非保守置信区间。例如，多道焊件会产生热影响区和脆性区，其局部特性与块状或焊接材料截然不同。厚型钢在表面附近也经常表现出一些性能变化。可能需要金相学和初步筛选来验证这些材料和类似级配材料的适用性。 第节 10.6 提供了一个筛选标准，以评估数据集是否不能代表宏观均匀的材料，因此可能不适用于本测试方法中采用的统计分析程序。如果数据集不符合筛选标准 10.6 ，使用中描述的分析方法可以更准确地评估材料的均匀性及其断裂韧性 附录X5 . 1.9 本标准并不旨在解决与其使用相关的所有安全问题（如果有的话）。本标准的使用者有责任在使用前建立适当的安全、健康和环境实践，并确定监管限制的适用性。 1.10 本国际标准是根据世界贸易组织技术性贸易壁垒委员会发布的《关于制定国际标准、指南和建议的原则的决定》中确立的国际公认的标准化原则制定的。 =====意义和用途====== 5.1 断裂韧性以弹塑性应力强度因子表示， K Jc ，这是从 J -断裂时计算的积分。 5.2 铁素体钢在微观上相对于单个晶粒的取向是不均匀的。此外，晶界具有不同于晶粒的性质。两者都含有碳化物或非金属夹杂物，可以作为解理微裂纹的成核位点。 这种成核位置相对于裂纹前缘位置的随机位置表现为相关断裂韧性的可变性 ( 13 ) 这导致断裂韧性值的分布，可以使用该测试方法中的统计方法进行表征。 5.3 该测试方法中的统计方法假设数据集代表宏观均匀的材料，因此测试材料具有均匀的拉伸和韧性。非均匀材料的断裂韧性评估不适用于本试验方法中采用的统计分析程序。例如，多道焊件会产生热影响区和脆性区，其局部特性与块状或焊接材料截然不同。 厚型钢在表面附近也经常表现出一些性能变化。金相分析可用于识别材料中可能的不均匀区域。然后，可以通过硬度、显微硬度和拉伸试验等机械测试来评估这些区域，以便与块体材料进行比较。还建议将这些不均匀区域的韧性特性与块体材料区分开来进行测量。第10.6节提供了一个筛选标准，用于评估数据集是否不能代表宏观均匀的材料，因此可能不适用于本试验方法中采用的统计分析程序。如果数据集不符合筛选标准 10.6 ，使用中描述的分析方法可以更准确地评估材料的均匀性及其断裂韧性 附录X5 . 5.4 分布 K Jc 来自重复测试的数据可用于预测 K Jc 对于不同的试样尺寸。理论推理 ( 9 ) 实验数据证实，4的固定威布尔斜率适用于所有数据分布，因此可以计算数据散布的标准偏差。数据分布和样本大小效应通过威布尔函数与最弱环节统计相结合来表征 ( 14 ) 定义了约束损失的上限和试验温度的下限，在这两者之间最弱- 可以使用链接统计。 5.5 实验结果可用于定义描述中值形状和位置的主曲线 K Jc 1T试样的转变温度断裂韧性 ( 15 ) 曲线在横坐标（温度坐标）上由实验确定的参考温度定位， T 0 参考温度的变化是例如由冶金损伤机制引起的转变温度变化的度量。 5.6 公差范围 K Jc 可以根据理论和一般数据进行计算。为了增加保守性，可以在公差范围内添加偏移量，以覆盖与估计参考温度相关的不确定性， T 0 ，来自相对较小的数据集。 由此，可以对以下内容进行利润调整 T 0 以参考温度偏移的形式。 5.7 对于某些材料，特别是那些低应变硬化的材料 T 0 由于裂纹尖端约束的部分丧失，可能会受到试样尺寸的影响 ( 5. ) 当此情况发生时 T 0 可能低于从以下数据集获得的值 K Jc 使用较大样本得出的值。 5.8 如文中所述 1.3 ，存在预期偏差 T 0 值作为标准试样类型的函数。随着数据集的平均裂纹尖端约束的减小，偏差的大小可能与给定屈服强度下测试材料的应变硬化能力成反比 ( 16 ) 平均而言， T 0 从C（T）试样中获得的值高于 T 0 从SE（B）试样中获得的值。最佳估计比较表明，C（T）和SE（B）之间的平均差 T 0 值约为10°C ( 2. ) 然而，单个C（T）和SE（B）数据集可能显示更大的 T 0 差异 ( 3. , 17 , 18 ) ，或SE（B） T 0 值可能高于C（T）值 ( 2. ) 另一方面，对单个小数据集的比较不一定能揭示这种平均趋势。包含C（T）和SE（B）样本的数据集可以生成 T 0 结果介于 T 0 仅使用C（T）或SE（B）试样计算的值。

1.1 This test method covers the determination of a reference temperature, T 0 , 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 ( 3.2.2 ) covered are those with yield strengths ranging from 275 MPa to 825 MPa (40 ksi 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 0 values as a function of specimen type for the same material. T 0 values obtained from C(T) specimens are expected to be higher than T 0 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 0 values is approximately 10°C ( 2 ) . C(T) and SE(B) T 0 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 0 results which fall between the T 0 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 0 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 0 is dependent on the K -rate. T 0 is evaluated for a quasi-static K -rate range with 0.5 < < 2 MPa√m/s. T 0 values for slowly loaded specimens ( < 0.5 MPa√m) can be considered valid if environmental effects are known to be negligible. Provision is also made for higher K -rates ( > 2 MPa√m/s) in Annex A1 . Note that this threshold K -rate for application of Annex A1 is a much lower threshold than is required in other fracture toughness test methods such as E399 and E1820 . 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 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 T 0 and nonconservative confidence bounds. 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. Metallography and initial screening may be necessary to verify the applicability of these and similarly graded materials. 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 . 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. ====== Significance And Use ====== 5.1 Fracture toughness is expressed in terms of an elastic-plastic stress-intensity factor, K Jc , that is derived from the J -integral calculated at fracture. 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 ( 13 ) . This results in a distribution of fracture toughness values that is amenable to characterization using the statistical methods in this test method. 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 ( 9 ) , confirmed by experimental data, suggests that a fixed Weibull slope of 4 applies to all data distributions and, as a consequence, standard deviation on data scatter can be calculated. Data distribution and specimen size effects are characterized using a Weibull function that is coupled with weakest-link statistics ( 14 ) . An upper limit on constraint loss and a lower limit on test temperature are defined between which weakest-link statistics can be used. 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 ( 15 ) . The curve is positioned on the abscissa (temperature coordinate) by an experimentally determined reference temperature, T 0 . Shifts in reference temperature are a measure of transition temperature change caused, for example, by metallurgical damage mechanisms. 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, T 0 , from a relatively small data set. From this it is possible to apply a margin adjustment to T 0 in the form of a reference temperature shift. 5.7 For some materials, particularly those with low strain hardening, the value of T 0 may be influenced by specimen size due to a partial loss of crack-tip constraint ( 5 ) . When this occurs, the value of T 0 may be lower than the value that would be obtained from a data set of K Jc values derived using larger specimens. 5.8 As discussed in 1.3 , there is an expected bias among T 0 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 ( 16 ) . On average, T 0 values obtained from C(T) specimens are higher than T 0 values obtained from SE(B) specimens. Best estimate comparison indicates that the average difference between C(T) and SE(B)-derived T 0 values is approximately 10 °C ( 2 ) . However, individual C(T) and SE(B) datasets may show much larger T 0 differences ( 3 , 17 , 18 ) , or the SE(B) T 0 values may be higher than the C(T) values ( 2 ) . On the other hand, 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 0 results which fall between the T 0 values calculated using solely C(T) or SE(B) specimens.