Paper presented at the 7th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Turkey, 19-21 July, 2010.
When designing of a new turboprop for appropriate flight conditions and requirements, the objective is to determine the optimum cycle parameters in terms of turbine inlet temperature (TIT) and compressor pressure ratio (CPR), in addition to the power turbine temperature ratio (TTR) that depends in how to divide gas enthalpy between shaft power and jet. However the selection of the best thermodynamic cycle for a turboprop engine is a very hard task, owing to many involved parameters and constraints. Thus, optimization tools are inevitable to explore the whole design space and to reach feasible solutions as quickly as possible. Furthermore, the design optimization of a turboprop cycle must be considered in view of mechanical design considerations.
While high TITs are thermodynamically desirable, they need using of expensive alloys and cooled turbine blades, leading to increased complexity and cost. On the other hand, higher pressure ratio must be considered in the issue of increased weight and complexity of the engine. Many studies were undertaken by several authors to determine the turboprop's optimum cycle parameters; all of them were based on parametric analyses, using extensive parameters variation. The present work focuses on the development of a numerical approach to select an appropriate turboprop engine matching with the power requirement of a given aircraft, and accordingly the optimum propulsion cycle parameters, involving two objectives (minimum fuel consumption and maximum power), in addition to several constraints. The optimization technique used herein is based on NSGA- II algorithm, which is a robust stochastic population based algorithm. The developed tool offers versatility in implementing a variety of operating conditions and objective functions, and considering technology constraints. Performance optimization of a gas turbine engine is defined to be one, or a combination of: minimizing fuel consumption while maintaining power levels, maximizing power and maximizing engine life by reducing turbine blade temperature while maintaining power levels. Combining these objectives for optimization led not to a single solution as considering each objective separately, because these objectives are generally conflicting. For example, reducing fuel flow will lead to reductions in thrust levels. A tradeoff surface is then determined (Pareto front)
without considering objective functions weighting, using NSGA- II algorithm, which uses Pareto dominance criteria. In the present study the objective function retained is a combination of performances cited above. So, we intend optimizing for the minimum fuel consumption and the maximum power at cruise, while maintaining a given takeoff power and a low entry temperature for low pressure turbine to account for engine life. Having takeoff power as an optimization constraint, that means our engine model must be able to operate at both design and off- design conditions. Finally, a set of alternative optimal solutions were obtained, and in view of additional subjective criteria, three design alternatives for the considered engine configuration of a given technology level are proposed. The obtained results illustrate the sensitivity of the engine performance analyser to both cycle parameters and design constraints.