Optimization of a multilayer thermal barrier coating system in a gas turbine combustion chamber with different operating conditions and coating properties
摘要
Gas turbine combustion chambers operate under extreme thermal and mechanical conditions, necessitating robust thermal barrier coating (TBC) systems for improved efficiency and durability. However, existing studies often address only one or two design parameters and typically lack a holistic optimization strategy under realistic engine conditions, limiting their practical applicability. To address this gap, the present study introduces a comprehensive multi-objective optimization framework for TBC systems using an orthogonal array design integrated with grey relational analysis. The main objective is to simultaneously minimize static stress, cyclic stress, and heat transfer in multilayer TBCs. A three-dimensional non-premixed combustion model is employed to simulate the internal flow and thermal field within a typical gas turbine combustion chamber, followed by an analytical–numerical model for evaluating thermo-mechanical behavior in the coating layers. Unlike previous approaches, which often relied on trial-and-error or single-response analysis, the proposed method considers multiple interacting variables and provides a systematic way to identify the optimal combination. Results indicate that operating pressure, topcoat thermal expansion coefficient, Young’s modulus, deposition temperature, and thermal conductivity are the most critical factors respectively. The optimal TBC configuration includes a topcoat thickness of 1.1 mm, oxide layer thickness of 5 μm, Young’s modulus of 300 GPa, thermal conductivity of 5 W m−1 K−1, thermal expansion coefficient of 5.6 × 10−6 K−1, deposition temperature of 1500 °C, operating temperature of 2000 °C, and pressure of 3 MPa. In addition, this study uniquely explores the effect of combustion chamber diameter on stress behavior, revealing that increased diameter reduces maximum static stress, reaching a minimum near 0.2 m. The highest uncertainty was observed in the TC layer (4.463 × 105), corresponding to approximately 0.01% of the estimated output. Overall, this work advances beyond existing methods by integrating comprehensive multi-response optimization and geometric analysis, thereby offering a more reliable and effective strategy for TBC design in advanced gas turbine systems.