Conclusions

In this study, elitism-based genetic algorithm method was applied for minimum specific fuel consumption of high-bypass turbofan engine in the conceptual design phase for different fuels. In this regard, TURBOGENf software program was developed. Decision variables in this software were the fan pressure ratio (nf) and the bypass ratio (a). The main conclusions drawn from the results of this study may be listed as follows:

• Depending on the application, it can be seen that elitism-based genetic algorithm method is a successful tool for solving this optimization problem.

• The ability of an elitism-based genetic algorithm to provide a family of optimal solution to this particular problem has been demonstrated.

• Optimization problem was solved easily in TURBOGENf.

• TURBOGENf can successfully solve optimization problems at 1.2 <nf < 2, 2<a< 10, and 23,000 <hPR (kJ/kg) < 120,000 with M0< 0.8.

• 3-D color-scaled surface performance plots of a high-bypass turbofan engine can be drawn easily from TURBOGENf.

• It can be observed that Gn>200, Pn>300, and Mr=0.003 are sufficient for yielding optimum points in TURBOGENf.

However, it has to be realized that the proposed application is rather academic. First, constrained problem could be considered. Then, additional effects such as the weight, noise, exergy efficiency, and thrust of the commercial engine or its pollutant emissions should be introduced in the model to define new figures of merit.

Nomenclature a0 Speed of sound at freestream, m/s

Cp Specific heat at constant pressure, kJ/(kg K)

Cr Crossover rate

Cv Specific heat at constant volume, kJ/(kg K)

e Polytrophic efficiency f Fuel-air ratio

F Thrust, kN

F/m 0 Specific thrust, N s/kg

GA Genetic algorithm gc Newton's constant

Gn Generation number has Sensitivity hPR Fuel heating value, kJ/kg

M0 Mach number at freestream

Mr Mutation rate

P Pressure, Pa

Pn Population number

R Universal gas constant, m2/(s2 K)

SFC Specific fuel consumption, g/(kN s)

T Temperature, K

V Velocity, m/s a Bypass ratio

Y Specific heat ratio n Pressure ratio Subscripts and superscripts c Compressor f Fuel; fan t Turbine

* Optimum

0,1,2,.. .,19 Different locations in engine stations

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