Comparative Study of Barrier Coatings on Turbine Blade Cooling

Abstract There is a continuous growth in various sectors of engineering and technology resulting in high demand for modern and innovative steps into providing solutions to overcome all barriers. With the increase in demand of modern age technology growing rapidly, the requirement of the advanced system has to keep up with this demand. The power required to drive such technology has one of its sources from the gas turbine propulsion system, which is capable to provide thrust and power to major components. In modern gas turbine applications, high power and thermal efficiency are of essential requirement. The two parameters that play a vital role in increasing the thermal efficiency of the gas turbine are its compression ratio and high turbine inlet temperature. The advanced gas turbine has inlet temperature, which exceeds the material thermal limitation of the blade. This high temperature has an impact on the performance and life of the blade employed for energy extraction in the turbines. The current study analyzes the methods dealing with increasing the cooling effectiveness of the turbine blade, which are working under very high-temperature hot gases that exit from the combustion chamber. This gas expands into the turbine region by which power is extracted. These high-temperature gases can have a considerable effect on the stresses developed that can lead to failure under the cyclic loading of these hot gases. Cooling effectiveness can increase the system working temperature from 800K up to 1000K inlet. The current research compares the means of reducing the heat transfer and improve cooling effectiveness with the help of the latest improved material coatings such as thermal barrier coatings (TBCs) and environmental barrier coatings (EBCs). The study focuses on the effect of these TBCs and EBCs employed on the surface of the blade. Analysis of results obtained from this conjugate heat transfer (CHT) study has shown good agreement with the experimental data. The comparison revealed the use of the SST k-ω model which was efficient and predicted similar trends as that of the experimental for pressure were as with 3% of deviation for temperature.