Dynamic Model Uncertainty Calculation Dataset

Compared to other energy sources, the nuclear reactor as a spacecraft power source possesses many advantages such as small size, high power density, and long operating life, which indicates nuclear power is an ideal energy for future deep space exploration. A whole system model of the space nuclear reactor is developed consisting of the reactor neutron kinetics, reactivity control, reactor heat transfer, heat exchanger and thermoelectric converter. In addition, an electrical power control system is designed based on the developed dynamic model. The GRS method is used to quantitatively calculate the uncertainty of coupling parameters of the neutronics, thermal-hydraulics and control system for the space reactor. The Spearman correlation coefficient is applied in the sensitivity analysis of system input parameters to output parameters. The calculation results show that the uncertainty of the output parameters caused by coupling parameters has the most considerable variation, and the relative standard deviation is less than 2.01%. Effective delayed neutron fraction is most sensitive to electrical power. To obtain optimal control performance, the Non-dominated Sorting Genetic Algorithm (NSGA-II) method is employed to optimize the controller parameters based on the uncertainty quantification calculation. Two typical transient simulations are carried out to test the adaptive ability of the optimized controller in the uncertainty dynamic system, including 100% Full Power (FP) to 90% FP step load reduction transient and 5% FP/min linear variable load transient. The simulation results show that, considering the influence of system uncertainty, the optimized controller could improve the response speed and load following accuracy of electrical power control, in which the effectiveness and superiority have been verified.