Data assimilation for the burnup distribution applying the three-dimensional variational and artificial neutral network algorithm

Abstract

In this paper, a data-assimilation method has been proposed and applied for the burnup distribution of PWR. The burnup distribution is significant for the safety and economy of the reactor, as it is essential for the fuel-reloading design and optimization. Due to the fact that the burnup distribution cannot be measured directly during the reactor operation, the numerical simulation is widely applied in reactor engineering. However, there definitely exist differences between the numerical simulation and the actual core due to some unavoidable factors, such as component manufacturing deviation, uneven flow distribution and so on. These differences would induce the errors to the simulation values of power distributions and hence to the burnup distributions. Therefore, a data-assimilation method for the burnup distribution has been proposed, aiming at reducing the burnup-distribution errors with application of the power-distribution measurements. In our research, the three-dimensional variational (3DVAR) algorithm was applied for burnup-distribution calibration and the artificial neutral network (ANN) algorithm was applied to establish the complex relations between burnup distribution and power distribution. As engineering verification, the proposed data-assimilation method has been applied to the CNP1000 PWR operated in China. The numerical results indicated that the burnup-distribution errors can be reduced notably, as the maximum value of relative errors for power distribution can be reduced from 9.53% to 5.11%.