During the conceptual design process of an engine, a thermodynamic cycle is initially defined. This is done to ensure that all aircraft requirements, defined in a number of discrete operating points, can be met. Critical component requirements can then be screened off from these operating points underpinning the conceptual design process. As an example, this has traditionally meant that aerodynamic sizing for low specific thrust turbofan engines occurs at top-of-climb and mechanical and temperature constraints are set at take-off.
By providing additional parameters indicating the level of technology assumed, such as diffusion factors and stage loadings, a basic geometric representation of the engine can be mapped out as part of the conceptual design process. However, by choosing the parameters representing the component technology levels explicitly, the ability to trade efficiency for weight, or efficiency for cost, becomes less potent. In general, an explicit parameter choice will mean that a suboptimal solution is found.
Hence, it makes sense to develop methods that allow including these technology parameters into the conceptual design and performance modeling process in a consistent way. If, for instance, component efficiency is modeled based on turbomachinery stage loading, including the stage loading parameters into the optimization means that the efficiency must be updated based on the stage loading variation. In general, a consistent method requires that conceptual design input is collected in a number of performance operating points, transferred into the conceptual design process and that output from the conceptual design process is returned to the optimizer.
To illustrate the consistent conceptual design and performance modeling process, turbomachinery component models are included in the paper, interrelating polytropic efficiency, Reynolds number, size effects and component entry into service. These equations are solved consistently in the conceptual design and performance modeling to establish an optimum year 2020 engine. The method is then further illustrated by comparing the year 2020 engine with two year 2030 engines. The first year 2030 engine is established by an optimization assuming fixed polytropic turbomachinery efficiencies. The other case is defined by assuming the same engine architecture, i.e., the same number of turbomachinery stages as the year 2020 engine. In this case, the efficiency modeling is done using a consistent conceptual design optimization. The consistent optimization produced a more efficient engine despite the fact that the stage numbers were limited to the year 2020 configuration. The benefit is obtained by more thoroughly exploring the pressure ratio distribution between the engine components, as a result of the consistent optimization methodology.