Distributed Electric Propulsion (DEP) is one of the unconventional airplane architectures of interest in the quest for decreasing aviation environmental footprint. This configuration integrates strong and innovative couplings between systems and aircraft design disciplines. To address limitations of the traditional approach for certification and of the associated means of compliance when certifying innovative products, the European Union Aviation Safety Agency (EASA) issues in 2017 a novel certification philosophy that relies on high-level objective-based safety requirements. In this context, this paper presents a safety and certifiability evaluation of DEP airplane in EASA CS-23 category, with a methodology for aircraft-level safety assessment during preliminary design, a certification gap analysis with regards to existing means of compliance, and some proposals to clear the certification path for DEP configuration.

In the frame of the European objectives in terms of CO2 emissions, the aeronautics is looking for a technological rupture to achieve them, in particular, the aircraft design domain pursuits this through the research of innovative architectures. One of these innovative configurations currently being explored includes the hybrid electric energy source (thermal/electric) for Distributed Electric Propulsion (DEP) architecture. This Paper details a code developed to size a general aviation aircraft at concept level, by only defining its top level requirements and the main architecture parameters. The code can manage both conventional and hybrid power source as well as concentred or distributed propulsion architectures in order to allow the user to evaluate and compare the feasibility and benefits respectively of these innovative architectures. This code is a branch of the code “FAST-CS25” (Future Aircraft Sizing Tool for conventional CS-25 type) held by ONERA/ISAE-SUPAERO. The presented work aims at the expansion of the FAST code to CS-23 conventional type, hybrid electric energy source, and distributed propulsion system configurations. Through this paper, the models and the main sizing loops for the concept design are described, but putting special emphasis on the distributed propulsion aerodynamics and wing mass estimation. These detailed models where validated with the NASA X-57 DEP aircraft satisfactory. The whole concept design loop of a hybrid energy aircraft was validated with the eGenius hybrid energy aircraft.

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In the context of reducing the environmental footprint of tomorrow’s aviation, Distributed Electric Propulsion (DEP) has become an increasingly interesting concept. With the strong coupling between disciplines that this technology brings forth, multiple benefits are expected for the overall aircraft design. These interests have been observed not only in the aerodynamic properties of the aircraft but also in the structural design. However, current statistical models used in conceptual design have shown limitations regarding the benefits and challenges coming from these new design trends. As for other methods, they are either not adapted for use in a conceptual design phase or do not cover CS-23 category aircraft. This paper details a semi-analytical methodology compliant with the performance-based certification criteria presented by the European Union Aviation Safety Agency (EASA) to predict the structural mass breakdown of a wing. This makes the method applicable to any aircraft regulated by EASA CS-23. Results have been validated with the conventional twin-engine aircraft Beechcraft 76, the innovative NASA X-57 Maxwell concept using DEP, and the commuter aircraft Beechcraft 1900.

Aircraft operational performance is a key driving factor to flight punctuality and airline profitability. The ability of a system to meet its operational requirements in terms of reliability, availability and costs is termed as ’Operability’. It is of high importance for aircraft manufacturers to project operability during the early stages of development of an aircraft in order to make trade-off studies. This paper proposes a hybrid approach of using machine learning and expert knowledge to aid the projection of aircraft operational performance during the early design stages. This approach aims to benefit from the huge amount of in-service data available from the current and past fleet of aircraft. Hence, machine learning techniques are used to learn how different technical issues and their associated maintenance activities impact aircraft operations. Expert knowledge is used to establish the default rules of the simulation model used for the operability projection. Results from machine learning are used to improve these rules allowing one to make holistic projections of the operational performance of future aircraft. This approach allows one to estimate the elapsed time in different operational states of an aircraft like flying, turn-around, etc. which can then be used to calculate different operability Key Performance Indicators (KPIs) like aircraft reliability and maintenance unavailability.

Current developments in preliminary design emphasise the potential benefit of addressing detailed sizing cases in the early design stages. This implies a sound understanding of the loads that the structure must withstand and for which it must demonstrate compliance. In aircraft structural practices, stringent safety requirements demand robust designs. It is understood that the foremost limitation and very challenging aspect, in the aviation sector, consists in complying with those requirements while targeting a contained mass. In this respect, the presented work aims to propose an automated implementation of the dimensioning chain by foregrounding a specific subsystem application, id est the Vertical Tail Plane. The conditions corresponding to a set of critical flight loads are identified and used for the sizing process. The use case intends to standardise the process, narrowing down the large number of unknowns on the overall loosely defined design method.

Nowadays, digitalisation of aircraft, of their operations and their support became a crucial component for all the market players of the aeronautical industry. This technical field occupies an increasingly significant place, due to the generation of a substantial volume and an extensive variety of operational data. This new trend suggests taking those data into account during preliminary design and certification steps, in order to include additional considerations during those phases, such as operational criteria, maintenance, added value, development times or certification delays. In that way, this paper aims at suggesting a methodology to consolidate the aircraft design and certification processes though the use of those novel “digital” resources.