Over the past decades of preliminary aero-engine design a great effort has been invested in increasing steady-state efficiency to reduce missions fuel burn and thus CO2 emissions. Whilst pushing the performance cycle further to its limits previously minor deemed processes such as the transient behavior become more important because engines stability must still be granted for. It is therefore beneficial to integrate transient performance early into the overall aero-engine design tool chain to be able to predict the dynamic behavior from the beginning.
This paper presents a methodology to couple predesign and transient performance simulation in order to get a more holistic picture of aero-engines early in the design process. This procedure entails extensive amount of data transfer throughout multi-disciplinary tools with different fidelity levels. This task is tackled using DLRs virtual engine platform GTlab (Gas Turbine Laboratory), which provides a geometric data model with abstract description of predesign components and standardized interfaces for data exchange. In order to demonstrate the proposed methodology a performance model of a turbofan similar to the V2500 aero-engine is used. For that purpose, a performance cycle is established providing boundary conditions for the preliminary aerodynamic engine design. The designed components provide necessary input data for the subsequent transient certification maneuver Eventually, parametric studies are conducted to show the impact of design variations on transient data such as the minimum surge margin and minimum tip clearance as well as on preliminary engine design.
The collaborative multi-disciplinary design of aircraft engines is a complex and highly iterative process. An essential characteristic of this design process is the involvement of a large number of experts from different disciplines, as well as the usage of numerous tools and workflows. Large amounts of data are produced and need to be exchanged via a multitude of interfaces. Furthermore, the data undergoes various transformations in the course of the design process. Understanding where a certain piece of data originates from and how it is connected to other datasets becomes therefore progressively essential. The purpose of this paper is to present a methodology to apply data provenance models in collaborative multi-disciplinary aero-engine design, supported by an approach for data standardization and identification. Besides the methodology, the software implementation to support this approach is presented in detail, including automated capturing and storage of provenance data, as well as methods for data investigation. In addition the presented methodology is evaluated by means of practical examples from the field of preliminary aero-engine design.
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