Content area
Double ceramic layer thermal barrier coatings (DLC-TBCs) are favored for combining the benefits of top and bottom ceramic materials. The thickness ratio of the top and bottom ceramic layers significantly impacts the performance of the DLC-TBCs. In the design process, it is generally desired to balance its thermal insulation properties with a long service life. Therefore, this study establishes a multi-objective parameter optimization design method based on NSGA-II to optimize the thickness of the CeYSZ/Al2O3 DCL-TBCs. Experimental verification of the coating performance was conducted based on the optimization results. Firstly, based on theoretical and numerical models, a quantitative analysis was conducted on the effects of the thickness of each material in the CeYSZ/Al2O3 DCL-TBCs system on thermal insulation and thermal stress. Space parameters were obtained using optimal Latin hypercube sampling, and a radial basis function (RBF) neural network surrogate model was constructed based on the numerical calculation results. Sensitivity analysis was employed to evaluate the impact of the total thickness of the TBCs and the thickness of the Al2O3 ceramic layer on the objective function. Finally, NSGA-II was utilized for optimization. The obtained Pareto optimal solution set was validated, showing that the performance of the CeYSZ 190 μm/Al2O3 120 μm DLC-TBCs satisfied the requirements. Therefore, TBCs of different thicknesses were sprayed and subjected to thermal insulation and thermal shock experiments. The results demonstrated that the optimized TBCs significantly improved service life without compromising thermal insulation, providing a new approach for the subsequent design of DLC-TBCs structures.
Details
Verification;
Coatings;
Sensitivity analysis;
Optimization;
Thermal insulation;
Protective coatings;
Thickness ratio;
Ceramics;
Service life;
Hypercubes;
Thermal barrier coatings;
Multiple objective analysis;
Design;
Stress concentration;
Heat conductivity;
Composite materials;
Thermal stress;
Neural networks;
Radial basis function;
Temperature;
Numerical models;
Thermal barriers;
Mathematical models;
Sensors;
Objective function;
Aluminum oxide;
Insulation;
Design optimization;
Parameters;
Thermal shock;
Latin hypercube sampling
1 Shanghai Jiao Tong University, Engineering, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293); Shanghai Jiao Tong University, National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293)
2 China North Vehicle Research Institute, Science and Technology on Vehicle Transmission Laboratory, Beijing, China (GRID:grid.464234.3) (ISNI:0000 0004 0369 0350)
3 Beijing Institute of Technology, School of Materials Science and Engineering, Beijing, China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246)
4 Shanghai Jiao Tong University, National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293)