The development of every new aero-engine follows a specific process; a sequence of steps or activities which an enterprise employs to conceive, design and commercialize a product. Typically, it begins with the planning phase, where the technology developments and the market objectives are assessed; the output of the planning phase is the input to the conceptual design phase where the needs of the target market are then identified, and alternative product concepts are generated and evaluated, and one or more concepts are subsequently selected for further development based on the evaluation. For aero-engines, the main goal of this phase is therefore to find the optimum engine cycle for a specific set of boundary conditions. This is typically done by conducting parameter studies where every calculation point within the study characterizes one specific engine design. Initially these engines are represented as pure performance cycles. Subsequently, other disciplines, such as Aerodynamics, Mechanics, Weight, Cost and Noise are accounted for to reflect interdisciplinary dependencies. As there is only very little information known about the future engine at this early phase of development, the physical design algorithms used within the various discipline calculations must, by default, be of a simple nature. However, considering the influences among all disciplines, the prediction of the concept characteristics translates into a very challenging and time intensive exercise for the pre-designer. This is contradictory to the fact that there are time constraints within the conceptual design phase to provide the results. Since the early 1970’s, wide scale efforts have been made to develop tools which address the multidisciplinary design of aero-engines within this phase. These tools aim to automatically account for these interdisciplinary dependencies and to decrease the time used to provide the results. Interfaces which control the input and output between the various subprograms and automated checks of the calculation results decrease the possibility of user errors. However, the demands on the users of such tools are expected to even increase, as such systems can give the impression that the calculations are inherently performed correctly. The presented paper introduces MTU’s preliminary design system Modular Performance and Engine Design System (MOPEDS). The results of simple calculation examples conducted using MOPEDS show the influences of the various disciplines on the overall engine system and are used to explain the architecture of such complex design systems.
An Intelligent/Learning Axial Fan Design System