A methodology for segmenting large metal components from nuclear power plants has been developed with a view to minimizing the number of containers to emplace segmented pieces. Spherocylinder-type and rectangular prism-type objects are modeled in shapes, and equations to calculate heights, widths, lengths, or angles for segmentation and the number of pieces are derived using geometric theorems, with a hypothetical ‘virtual rectangle’ being introduced for simplification. Applicability of the new methodology is verified through case studies assuming that each segmented piece is packaged into a 200 L container, and a procedure for adjusting potential overestimation of the segmented pieces due to the virtual rectangle is proposed. The new approach results in fewer segmented pieces but more containers than an existing segmentation study using 3D modeling. It is demonstrated that the number of containers can be further reduced, however, if the generalized methodology is followed by 3D modeling. In addition, it is confirmed that the generalized approach is also applicable to a nonstandard shapes such as ellipsoidal shape but only under limited conditions. Sensitivity analyses are conducted by changing dimensions of the objects and container, which brings about an optimal dimension of container as well. The generalized approach would be utilized either alone in decommissioning planning to estimate waste from segmentation of large metal components or combined with 3D modeling to optimize segmentation operation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.