Environmental Design Space model assessment

Abstract

The Environmental Design Space (EDS) is a multi-disciplinary design tool used to explore trade-offs among aircraft fuel burn, emissions, and noise. This thesis uses multiple metrics to assess an EDS model of a Boeing 777 aircraft. Starting from a detailed description of the EDS framework, a description of EDS model creation is outlined. The aircraft and engine model is assessed by a comparison to an industry-developed model and changes to the EDS model are explored to improve the model's predictive ability. The model is assessed by sensitivity studies on the inputs, component performance maps, and constraints. An alternate method of applying additional constraints to EDS results is also investigated. Finally, the model uncertainty is quantified using Monte Carlo simulations. This includes a study where all the inputs are varied and a study which investigates the implications of model uncertainty on trade study results. The comparison to the industry model shows that optimization around three design points is required to develop a model of acceptable accuracy.

(cont.) The input sensitivity study shows that there are only a few key drivers to the EDS model, but the direction of the trends with some of these variables is counterintuitive due to the typical practice constraint of holding the aircraft thrust to weight ratio constant. The constraint sensitivity study reveals there are only a handful of constraints implemented in EDS and the current method for applying additional constraints can increase the resultant errors due to the response surfaces generated. The uncertainty studies reveal the implications of attempting to correct cases which would otherwise fail and how fixes can skew results and increase uncertainty. Finally, the trade study uncertainty analysis shows that EDS is capable of answering questions with higher confidence than one would assume from the results of the input uncertainty study since the uncertainty due to variables which are not changing in a trade study are not significant.