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In this paper we explore the crucial role played by the use of large databases in the identification, development, and refinement of models that describe the toughness behavior of ferritic steels. Specifically, we seek to emphasize and illustrate the point that when physical models are calibrated using large databases this process can reveal trends not previously seen, or foreseen. In support of this idea two examples are cited. First, the evidence for a CVE master curve in fracture mode transition is reviewed, as a counterpoint to the commonly held belief that each Charpy tanh transition curve is unique, with little commonality even within specific alloys, let alone across all ferritic steels. Second, new evidence is presented that the degree of prior hardening experienced by a ferritic steel has a systematic effect on the scatter exhibited by KJc data. This evidence suggests that the KJc Master Curve model, in which the scatter of KJc follows a Weibull distribution having a Kmin = 20 MPa√m and a slope (scatter magnitude) of 4, requires refinement, especially for the higher To values characteristic of steels that have been hardened by, for example, neutron irradiation damage.Copyright © 2009 by ASME

In the 1960s and 1970s when the surveillance programs for currently operating commercial nuclear reactors were established state of knowledge limitations resulted in the use of Charpy-V notch (CVN) specimens rather than fracture toughness specimens. Reasonable success has since been achieved in correlating CVN and fracture toughness parameters. Such correlations provide an important part of the technical basis for both current regulations and ASME codes. These correlations imply that trends manifest in CVN data must also appear in fracture toughness data even though empirical evidence demonstrates that this is not always true. For example, the temperature dependence of CVN energy (CVE) in transition is thought to be a unique feature of each specific sample of ferritic steel that is tested, a view in sharp contrast with the now widely accepted view of a “Master Curve” for transition fracture toughness (KJc). Also, effects of product form on CVE temperature dependence and property correlations are widely reported despite the fact that product form effects are absent from KJc properties. These observations suggest that the mapping of CVE behavior onto fracture toughness implicit to correlation-based regulations and ASME codes may produce erroneous trends in estimated values of fracture toughness. In this paper we investigate the hypothesis that the apparent differences between CVE and fracture toughness arise due to differences in how the temperature dependence of CVE and KJc data have historically been modeled. Our analysis shows that when CVE data are analyzed in a manner consistent with KJc data (i.e., transition and upper shelf data are partitioned from each other and analyzed separately rather than being fit with a continuous tanh function) the apparent differences between CVE and toughness characterizations are minimized significantly, and may disappear entirely. These findings demonstrate the differences between CVE and fracture toughness data to be an artifact of the tanh analysis method rather than an intrinsic property of CVE.

Models to predict the fracture and arrest behavior of ferritic steels have long been under development. The current, most widely accepted model of fracture toughness behavior is the ASTM E1921-02 “Master Curve” that is used to predict the variation of the median cleavage fracture toughness (KJc) with temperature in the transition temperature region, as well as predicting the scatter of data about the median at any given temperature. Recently, models describing the variation of crack arrest fracture toughness (KIa) and of ductile initiation fracture toughness (JIc) with temperature have also been proposed. Moreover, models are also available that relate these various temperature dependencies to each other, and relate them all a common parameter, the cleavage crack initiation fracture toughness index temperature To. Research work continues to better quantify these relationships and to more firmly understand their physical bases. Nevertheless, the ample empirical evidence on which the models are based and the existing physical understanding underlying the models suggests that they can be used as a tool in both fitness-for-service assessment and in the design of experiments conducted to investigate the fracture toughness of ferritic materials. While still being developed, these toughness-based models offer clear advantages relative to alternative (correlative) approaches in terms of reduced prediction uncertainty. In this paper we amalgamate the results of previous publications to provide an algebraic expression for the variation of KJc, KIa, and JIc with temperature that includes explicit quantification of the uncertainty in each variable. We also discuss the implications and potential applications of this combined model.