Genetic algorithm based temperature control of the dense granular spallation target in China initiative accelerator driven system

Abstract The DGT (Dense Granular spallation Target) is the crucial component in CiADS (China initiative Accelerator Driven subcritical System), which is the important device in connecting the high power accelerator and the subcritical reactor. In order to keep the stable and reliable running of the coupling system, the temperature control of the DGT should be carefully studied and optimized, where the gravity driven tungsten alloy granules are considered as the spallation target material and the corresponding coolant, and the working temperature in normal operation condition should be controlled around the pre-setting value without bringing the large perturbation. Two kinds of control approaches have been adopted in this research in adjusting the temperature inside the DGT, which are the intensity of proton beam and the flow speed of tungsten alloy granules. Therefore, the simulation method and the PID (Proportional Integral Derivative) controller have been established based on the cooperation of two approaches in order to better adapt to the temperature control of the DGT. Moreover, the genetic algorithm has been employed to select and optimize the key parameters in PID controller for the purpose of substituting the experiential selection in traditional manually iterative process. Finally, the temperature control system has been evaluated based on the reference control scenarios, and all the simulation results demonstrate that the optimized method has applicability and feasibility in the temperature control of the spallation target system.