The integration of an efficient high lift system in the design process of a blended wing body aircraft

The Advisory Council for Aeronautics Research in Europe (ACARE) set ambitious goals for the aeronautic community to be reached by 2050. With the targets being high, only new aircraft concepts, incorporating advanced engine and material technologies will be able to meet the challenge. In this context, the ACFA 2020 (Active Control for Flexible Aircraft 2020) was initiated in 2008 as a collaborative research project for innovative aircraft concepts funded by the European Commission (FP7). The project consortium consisted of eleven research institutes including the European Aeronautic Defence and Space Company (EADS). The designed blended wing body (BWB) is the aircraft platform for further analysis in this paper. In order to analyze the low speed phase in detail, the paper describes the configuration design process and the adaptation of design methodologies to the special problem of selecting and analyzing an efficient high lift system. The methodologies used comprise numerical analysis for aerodynamics and structure as well as multidisciplinary design optimization (MDO). The integration of an advanced high lift system requires an aerodynamically carefully designed solution. Sufficient lift needs to be achieved with a limited impact on the moment balance. A trimmed condition is difficult to achieve without a horizontal tail and in view of shorter lever arms to counteract moment balance changes through camber variations. Structure wise, the integrative effects are also closely coupled with BWB aircraft. A down selection of an appropriate leading and trailing edge high lift system led to the dimensioning and simulation of a combined system within the design process described in the paper. The computational fluid dynamics (CFD) results for an advanced combined trailing and leading edge system with active support are presented in the context of the overall aircraft concept. The system is optimized using gradient-based optimization. Weight and cost estimates are discussed at the end.