Evaluation of Fracture Toughness of a SA580 Gr. 3 Reactor Pressure Vessel Using a Bimodal Master Curve Approach

The standard master curve (MC) approach has a major limitation in that it is only applicable to homogeneous datasets. In nature, steels are macroscopically inhomogeneous. Reactor pressure vessel (RPV) steel has different fracture toughness with varying distance from the inner surface of the wall due to the higher cooling rate at the surface (deterministic material inhomogeneity). On the other hand, the T0 value itself behaves like a random parameter when the datasets have large scatter because the datasets are for several different materials (random inhomogeneity). In this paper, four regions, the surface, 1/8 T, 1/4 T, and 1/2 T, were considered for fracture toughness specimens of Korean Standard Nuclear Plant (KSNP) SA508 Gr. 3 steel to provide information on deterministic material inhomogeneity and random inhomogeneity effects. Fracture toughness tests were carried out for the four regions at three test temperatures in the transition region and the microstructure of each region was analyzed. The amount of upper bainite increased toward the center, which has a lower cooling rate; therefore, the center has lower fracture toughness than the surface so reference temperature (T0) is higher. The fracture toughness was evaluated using the bimodal master curve (BMC) approach. The results of the BMC analyses were compared with those obtained via a conventional master curve analyses. The results indicate that the bimodal master approach considering inhomogeneous materials provides a better description of scatter in the fracture toughness data than a conventional master curve analysis does.

Fracture Toughness Assessment of SA508 Gr 3 Steel for KSNP RPV Using Conventional and Bimodal Master Curve Approaches

The standard master curve approach has the major limitation, which is only applicable to homogeneous datasets. In nature, steels are macroscopically inhomogeneous and thus the fracture toughness has larger scatters than expected by a conventional master curve approach. RPV steel has different fracture toughness with varying distance from the inner surface of the wall. Regarding this, a clear tendency was reported in that the toughness extracted near the surface had to be higher than in the center region due to the higher quenching rate at the surface (deterministic material inhomogeneity). On the other hand, the T0 value itself behaves like a random parameter when the datasets have a large scatter due to the datasets consisting of several different materials such as welding region (random inhomogeneity). In the present paper, four regions, the surface, 1/8T, 1/4T and 1/2T, were considered for fracture toughness specimens of KSNP (Korean Standard Nuclear Plant) SA508 Gr. 3 steel to provide deterministic material inhomogeneity and random inhomogeneity effect. Specimens were extracted from these four regions and fracture toughness tests were performed at various temperatures in the transition region. Several concepts were provided for the master curve of inhomogeneous materials such as a bimodal and random inhomogeneous master curve scheme, and among them, the bimodal master curve analyses were reviewed and compared with a conventional master curve approach to find the random inhomogeneity. The bimodal master curve considering inhomogeneous materials provides better description of scatter in fracture toughness data than conventional master curve analysis, but it is unclear to provide evidence that the bimodal analysis lines follow the data more closely than the conventional master curve analysis.