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At this time, the system with advanced automatic detection capability has consistent execution results and has been verified that it can be used as a necessary tool for cost reduction and the quality control of the product, which is the value of the customer. It will contribute to reducing human error and minimizing defects by designing a system that relies on more mechanization automation, taking into account the characteristics of the machine as well as the role of humans and machines.

The adjoint-weighted perturbation (AWP) method, in which the required adjoint flux is estimated in the course of Monte Carlo (MC) forward calculations, has recently been proposed as an alternative to the conventional MC perturbation techniques, such as the correlated sampling and differential operator sampling (DOS) methods. The equivalence of the first-order AWP method and first-order DOS method with the fission source perturbation taken into account is proven. An algorithm for the AWP calculations is implemented in the Seoul National University MC code McCARD and applied to the sensitivity and uncertainty analyses of the Godiva and Bigten criticalities.