The meta-heuristic method based cutting planning for the decommissioning of spallation target in China initiative accelerator driven subcritical system

The decommissioning of high power spallation target in China initiative accelerator driven subcritical system (CiADS) has been considered as the tough and important task that is directly related to the nuclear safety supervision of the coupling facility and the radiation protection management for the transportation procedure. In the retirement stage, the high radioactive spallation target with large volume and complex structure should be cut into some pieces with different sizes according to the distribution of radiation dose, and then all the radioactive nuclear structures need to be packed into different volumes of high integrity containers for the security storage. In order to fulfill the decommissioning of spallation target system, the optimization method for the cutting planning has been proposed in this research work, where the voxelization technology has been used to describe the complex spallation target model. Moreover, the genetic algorithm has been employed to select the appropriate voxel grids in obtaining different groups of geometries based on the accepted radiation dose, and then the optimized cutting paths for the spallation target will be reconstructed based on the information of different voxelized groups with the intuitive visualization feature. Finally, the applicability and feasibility of the optimization cutting planning method have been tested in the scenario of splitting the spallation target into small pieces, where all the simulation results demonstrate that the proposed optimization method can meet the decommissioned requirements and can be used for the spallation target system. CO 2022 Published by Elsevier Ltd.