15th European Conference on Turbomachinery Fluid dynamics & Thermodynamics

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Oliver Sjögren  - Chalmers University of Technology, Göteborg, Sweden
Tomas Grönstedt - Chalmers University of Technology, Göteborg, Sweden
Carlos Xisto - Chalmers University of Technology, Göteborg, Sweden
Anders Lundbladh - Chalmers University of Technology, Göteborg, Sweden; GKN Aerospace, Trollhättan, Sweden


One of the challenges when designing fan stage components for low specific thrust turbofan engines in aircraft applications, is how to rank the component level attributes. From a system-level perspective, objectives and requirements on a component-level are generally determined by its relationship with other interfacing sub-systems and system-level objectives. However, it is also important to have access to accurate information about interdependencies between certain component attributes, as well as limitations of the technology, early in the design phase in order to make successful decisions regarding the system level architecture in the first place. In modern turbofan engines the bypass section of the fan stage alone provides the majority of the total thrust in cruise and the size of the fan has a considerable effect on overall engine weight and nacelle drag. Thrust requirements in different parts of the flight envelope must also be satisfied together with sufficient margins towards stall. An accurate description of the interdependencies of relevant performance and design attributes of the fan stage alone – such as pressure ratio, efficiency, weight, nacelle drag and surge margin – are therefore necessary to estimate system level objectives such as mission fuel burn and direct operating cost with enough confidence during the conceptual design phase. Due to a lack of information about the system level at this stage, the preference for a given fan stage attribute (e.g., whether it should be maximized or minimized) might be unknown. The contribution of this study is to apply a multi-parametric, multi-objective optimization approach to the detailed design of fan stages for geared low specific thrust turbofans with the intention to generate a set of pareto dominant designs that span conflicting attributes as well as additional attributes (or parameters) without preference ordering. The trade-offs between fan stage attributes are then modelled by parameterizing the multi-dimensional set of pareto frontiers and adapting a response surface to the data set, so that it can be incorporated as a performance model into a subsequent system level optimization.

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