scholarly journals Microstructure characterization of reactor pressure vessel steel A508-3 irradiated by heavy ion

2021 ◽  
Vol 2133 (1) ◽  
pp. 012015
Author(s):  
Xianfeng Ma ◽  
Meng She ◽  
Wenqing Zhang ◽  
Ligang Song ◽  
Shui Qiu ◽  
...  

Abstract As one of the key structures used in nuclear power plants, the study of irradiation effects of pressure vessel steel (RPV) is of great scientific value to nuclear safety. The RPV steel was irradiated by Fe ions up to three different irradiation damage levels (0.08 dpa, 0.15 dpa, and 0.6 dpa). The transmission electron microscope was utilized to measure the irradiated microstructure and it was found that after the irradiation of 0.08 dpa, the density and size of dislocation loops in Fe ions irradiated samples was small and the dislocation loops were distributed near the surface. When irradiation dose was up to 0.15 dpa, many black dots were distributed in the whole irradiation region and some large size dislocation loops appeared. In the case of 0.6 dpa, a large number of dislocation loops were produced and the distribution of dislocation loops extended to the whole irradiation region owing to the production and growth of defects such as vacancies and black dots.

2017 ◽  
Vol 23 (2) ◽  
pp. 376-384 ◽  
Author(s):  
Kristina Lindgren ◽  
Krystyna Stiller ◽  
Pål Efsing ◽  
Mattias Thuvander

AbstractRadiation induced clustering affects the mechanical properties, that is the ductile to brittle transition temperature (DBTT), of reactor pressure vessel (RPV) steel of nuclear power plants. The combination of low Cu and high Ni used in some RPV welds is known to further enhance the DBTT shift during long time operation. In this study, RPV weld samples containing 0.04 at% Cu and 1.6 at% Ni were irradiated to 2.0 and 6.4×1023 n/m2 in the Halden test reactor. Atom probe tomography (APT) was applied to study clustering of Ni, Mn, Si, and Cu. As the clusters are in the nanometer-range, APT is a very suitable technique for this type of study. From APT analyses information about size distribution, number density, and composition of the clusters can be obtained. However, the quantification of these attributes is not trivial. The maximum separation method (MSM) has been used to characterize the clusters and a detailed study about the influence of the choice of MSM cluster parameters, primarily on the cluster number density, has been undertaken.


2017 ◽  
Vol 488 ◽  
pp. 222-230 ◽  
Author(s):  
Kristina Lindgren ◽  
Magnus Boåsen ◽  
Krystyna Stiller ◽  
Pål Efsing ◽  
Mattias Thuvander

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