SHAPE OPTIMIZATION OF TURBINE NGV BY USING CFD COMPUTATIONAL TOOL

The most critical parts of a gas turbine engine are turbine blades and disc. They are designed to operate under severe conditions such as high turbine inlet temperature, high speeds, and high compression ratios. Owing to these operating conditions high rotational speed which is likely to be between 60000 and 100000 rev/min. Design optimization of fluid machinery based on computer simulation has become a reality today because of development of high speed computers. Highly complex flow patterns are being predicted by solving mass, momentum and energy equations and near accurate solutions at an acceptable level can be achieved. The present work aims at optimizing the blade shape and analysis of surrogate model of turbine blade. The sweep and lean variables are modified to enhance the efficiency, based objective. RANS equations are solved to get the flow field and objective function values. Based neural network, model has been constructed and the blade shape has been modified to enhance the performance. The surrogate performances are evaluated for applicability in turbo machinery blade