A case study of inaccuracy of advanced SAM application in the OPR1000

KHNP has developed a constrained simulated annealing method to account for the weakness of the least square method when using the SAM calculation for applications related to the OPR1000. The SAM is generated and installed once at the beginning of each cycle. Thus, the accuracy of ASI simulation by CPC is wholly dependent on the accuracy of the SAM constants. As the depletion proceeds, the deviation of the CPC axial power shape increases. When noise is included, the measurement data frequently exceeds the limit (8%) of the CPC ASI deviation. Therefore, KHNP has developed a constrained simulated annealing method to filter the noise from the measurement data and give the SAM a physical meaning. These two objectives form the core of the developed method. The least square method makes it difficult to implement the algorithm for filtering the noise. Thus, a mathematical method that has been used and verified in a variety of fields was adopted for the simulated annealing . In this paper, the relationship between the SAM and CPC axial power shape deviation is analyzed, based on results showing that EOC CPC axial power shape deviation has approached the limit (8%) in the OPR1000 when the simulated annealing method was applied