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Supercritical carbon dioxide (SCO2) Brayton cycle microturbine can be used for the next generation of solar power. In order to comprehensively optimize the supporting system and cooling device parameters of Brayton cycle shafting, the concept of chaos interval is introduced by chaotic mapping, and the CIMPSO algorithm is proposed to optimize the multi-objective rotor system model with nonlinear variables.The results show that the resonance amplitude of the optimized model is effectively attenuated, and the critical speed point is far away from the working speed, which shows the robustness of the optimization algorithm. Finally, based on arbitrary several sets of optimization solutions and empirical parameters, the finite element model of shafting is established for simulation, and the results show that the optimized solution has certain guiding significance for the design of the rotor system.The cooling device is designed and simulated by CFD method based on the optimal solution set. Both the inlet boundary conditions of given pressure (1 MPα) and given mass flow rate (0.1 kg/s) numerical calculations were carried out to characterize the cooling performance, for different jet impingement configurations ( H   r  / d   in   = 0.0125 ∼ 5).Several sets of analyses show the strong effects of the jet-to-target spacing ( H   r  / d   in  ) on the rotor thermal performance at a given diameter ( d   in  ) of the nozzle. Average temperature ( T   c  ) at the free end of the rotor show that, as jet-to-target distance decreases (0.0125 ≤  H   r  / d   in   ≤ 0.33), the heat dissipation efficiency of the cooling device with the given pressure boundary condition tends to decrease, while the conclusion is opposite when the inlet boundary condition is set to the given mass flow rate. And there is an interval for the optimal combination ( H   r  / d   in  ) to promote the cooling efficiency.

Optimal design to control rotor shaft vibrations and thermal management on a supercritical CO2 microturbine