Analysis Of Aircraft Configurations Including Propagated Uncertainties
When analysing the potential of novel aircraft configurations on a conceptual to preliminary design level, the often limited amount of time available for investigating physical properties of design candidates dictates both the low fidelity level and amount of analyses that can be conducted. The increase in computational power over the last decades has resulted in an increase in analysis capabilities for assessing aircraft concepts. However, considerations based on analyses using methods representing high-fidelity physics-based analysis still find their application in detailed design phases only. To create a proper basis for making design decisions in early design phases using the limited available information on the aircraft physics, supplementing that information by the uncertainty of the implemented analyses is required. The DLR project “Future Enhanced Aircraft Configurations (FrEACs)” is aimed at extending the early design phase with this required uncertainty information. The current paper investigates the analysis of aircraft configurations under consideration of propagated uncertainties in early design stages. Aside investigating sensitivities of the physical properties of aircraft, the propagation of uncertainties between individual modules in analysis workflows allows for determination of the overall uncertainty of these properties. The base for making well-grounded design decisions in conceptual and preliminary design stages is thereby improved. In order to propagate uncertainties across multiple analysis tools, at first uncertainties have to be determined at the individual tool level. In a parallel publication , this uncertainty determination is described for the disciplinary analysis modules within a low-fidelity physics based aerospace toolkit . According to the analysis question at hand, workflows are built up by connecting these modules in the distributed integration environment RCE . In this way, an analysis process is generated for the evaluation of target functions on OAD level. Aircraft geometrical parameters, analysis results and uncertainty data are exchanged using the Common Parametric Aircraft Configuration Scheme (CPACS) . Figure 1 shows an example of a workflow including uncertainty propagation components. Analysis modules are repetitively called to determine the sensitivities of input parameters with corresponding uncertainty band on its output parameters. In the final paper, three aircraft configurations for a short-to-medium range design mission are analysed and compared: a conventional aircraft for reference purposes and a strut-braced wing; depicted in Figure 2. After setting-up the workflows and comparing results of the reference aircraft to available data for a standard short to medium range design mission for calibration purposes, physical correlations of the configurations are investigated for short range design missions (about 1000nm). Analysis studies are performed to assess the potential in increasing aircraft fuel and cost efficiency for a constant set of design requirements. In determining the saving potential of the aircraft concepts, not only the absolute values of the figures of merit are compared, but also the uncertainty in the determination of these metrics. This offers the possibility to not only state that one concept is preferred above another, but especially with which level of certainty such a statement can be made.