Optimization the TIT profile in an annular combustion of a turbojet engine based on smart modeling and CFD simulation

Abstract

In this research, the turbine inlet temperature (TIT) profile optimization of an annular combustion chamber in a turbojet engine is studied based on the computational fluid dynamic (CFD) simulation- artificial neural network (ANN)- genetic algorithm (GA). This loop is named smart modeling and CFD simulation. The pattern factor (PF) is the maximum deviation of the engine temperature profile in the worst conditions. The turbojet engine performance is estimated by mass parameter (MP) of 0.17 at the design point by changing the dilution holes in order to optimizing the turbine inlet temperature profile's uniformity. Two different optimized designs are presented based on the changing of dilution holes geometry to assess the TIT profile in the turbojet engine. Their position and geometry of the primary zone (PZ) and secondary zone (SZ) and holes at the dilution zone (DZ) assumed constant. There is a row of cooling holes with 0.6 mm diameter in DZ. Thus, the effect of changing the inner diameter of dilution holes was studied by proposing two optimized different designs with different equivalent dilution. Three-dimensional numerical simulation results show that the Max.TIT are 1816.80, 1650.46 and 1540.69 in the basic design (BD) and the first and the second optimized design (OPTD1, OPTD2) respectively. Based on the Max.TIT quantity, PF are equal 0.81, 0.60 and 0.45. The comparison of the numerical simulation and experimental investigation results show that the TIT for the OPTD2 in the design point is 1203.04 K and 1227 K, respectively. The error percentage is about 2.87%.