(Received 12 April 2005; accepted 13 July 2005)
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A508 Grade 4N is a high nickel (3.4%) pressure vessel steel with a relatively high yield strength (585 MPa minimum for Class 1) and a relatively low transition temperature (47 J transition temperature of −29°C or below). Published fracture toughness data on this steel are nonexistent, and so they have not been included in prior assessments of the applicability of the Master Curve approach to pressure vessel steels. The purpose of this study is to compare the temperature dependence and data scatter for this steel with the behavior predicted by the Master Curve. The available database consists of approximately 800 fracture toughness tests on 51 material heats, some of which were given a temper embrittling heat treatment. As an additional basis of comparison, test data on A508 Grades 2 and 3, 1% nickel weld metal, and several high nickel (1.3–3.8%) steels (NiCrMo and NiCrMoV) were included in the assessment. Maximum likelihood techniques were used to fit the toughness data, and Monte Carlo methods were used to assess the observed distribution of Weibull slopes (related to the extent of variability). The results of this assessment show that the Master Curve provides a good description of the shape (temperature dependence) of the toughness curve for moderate and high transition temperatures. However, for heats with low transition temperatures below the range observed in other pressure vessel steels, the shape of the toughness curve deviates from the Master Curve. The lower the transition temperature, the larger the deviation from the Master Curve. Based on the test data, a model describing the behavior of A508 Grade 4N has been developed. This model also accurately describes the toughness behavior of the other pressure vessel steels included in this study. With respect to variability, the Weibull slope of A508 Grade 4N is consistent with the value of four prescribed by the Master Curve. However, the Weibull slope for the other pressure vessel steels included in this assessment is close to 3.4. This lower value of the Weibull slope, which indicates larger variability, is likely the result of material inhomogeneity.
Principal Engineer, Bechtel Bettis, Inc., West Mifflin, PA
Stock #: JAI13230