Development of a durability evaluation model to optimize rare-earth-element-based thermal barrier coatings

Abstract

Abstract A reliable technique for evaluating the durability of the double-ceramic-layered thermal barrier coatings will enhance the design process by increasing efficiency and lowering costs. In this study, a failure index was proposed, and a numerical model to evaluate the durability of the coating system was developed. The failure index is a factor that indirectly expresses durability by considering fracture toughness, thermal stress, and the specifications of the system. This approach was used in extensive parametric studies on the top coating material and the thickness ratio of coating systems exposed to temperatures in the range of 1200–1500 °C . For the reliability of the study, La2Zr2O7, La2Ce2O7, LaTi2Al9O10, and Sr(Zr0.8Yb0.1)O2.95 were considered as the material for top-coats. In addition, the heating/cooling condition was carefully determined to reflect an actual engine condition. The minimum thickness, the average shielding performance of the materials, and the failure indexes were calculated in this parametric study. The La2Ce2O7-based system and LaTi2Al9O10-based system were found to be the most effective insulation system and the most durable system, respectively. Finally, experimental studies on four kinds of materials were collected from the references. From the collected data, the failure index of each case was calculated and compared with the actual lifetime. As a result, we have confirmed that the log-scaled lifetime and failure indexes are in a linear relationship. Using the linear relationships, the failure index from the parametric study was converted to a lifetime, allowing for an intuitive durability comparison. In terms of converted life expectancy, the LaTi2Al9O10-based system was again found to be the most durable. In conclusion, the proposed failure index is a useful factor to express the durability of double-ceramic-layered thermal barrier coatings and its practicality can be enhanced by comparisons with experimental data.