Multi-objective optimization of a small turbojet engine energetic performance

Application fields of small turbojet engines (STJE) have been increasing day by day due to their superior features such as high power to weight ratio and reliability. In this study, parametric cycle analysis peculiar to STJE is implemented for different design variables such as compressor pressure ratio (CPR), turbine inlet temperature (TIT) as well as ambient temperature (T0). Based on these evaluations, several performance metrics of STJE are dealt with together by applying three different methods such as multi-objective genetic algorithm (MOGA), particle swarm optimization (MOPSO) and grey wolf optimization (MOGWO) under five analyses. According to performance analyses, net thrust of the STJE has improvement from 3.2 kN to 5.41 kN due to the increased TIT whereas it deteriorates from 4.87 kN to 4.67 kN due to the elevated CPR. However, with effect of the higher TIT, specific fuel consumption (SFC) of the STJE ascends from 42.96 g/kNs to 49.04 g/kNs while it diminishes from 39.57 g/kNs to 31.5 g/kNs owing to the higher CPR. The higher T0 leads net thrust to lower but the higher SFC. According to optimization findings at fourth analysis, the lower SFC is obtained with 31.51 g/kNs by MOGA than the other methods where SFC is 33.11 g/kNs whereas the higher net thrust is obtained with 6.209 kN by both MOPSO and MOGWO than the findings of MOGA where net thrust is 4.68 kN. When considering five optimization analyses, the findings of MOGA, MOGWO and MOPSO could be utilized depending on aircraft mission that turbojet engine requires to perform. It is thought that performing of multi-objective optimization could help in designing turbojet engines to the engineers.