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Advanced commercial aircraft increasingly use more composite or hybrid (metal and composite) materials in structural elements and, despite technological challenges to be overcome, composites remain the future of the aviation industry. Composite and hybrid aircraft today are equipped with digital systems such as fly by wire for reliable operations no matter what the flying environment is. These systems are however very sensitive to electromagnetic energy. During flight, aircraft can face High Intensity Radiated Fields (HIRF), static electricity, or lightning. The coupling of any of these threats with airframe structure induces electromagnetic energy that can impair the operation of avionics and navigation systems. This paper focuses on systems susceptibility in composite aircraft and concludes that the same electromagnetic rules dedicated to all metal aircraft for systems and wiring integration cannot be applied directly as such for composite aircraft.

Implementing Design for Environment (DfE) into the design process requires a strategic integration. Furthermore, as DfE is continuously evolving, flexible processes need to be implemented. This article focuses on the integration of DfE into an optimization framework with the objective of influencing next-generation aircraft. For this purpose, DfE and Structures groups are developing together a set of new environmental indicators covering all life cycle stages of the product by coupling a list of yes/no questions with an environmental matrix. The following indicators are calculated: Regulation risk, Impact of manufacturing the part, CO2 emissions and Recyclability potential. These indicators will be used as constraints in the multi-disciplinary design optimization (MDO) framework, meaning that the structure will be designed while complying with environmental targets and anticipating future regulation changes.

Current transport aircraft are mature systems, thus require increased fidelity at the beginning of the design process to allow further optimization. Furthermore, a desire exists to explore unconventional aircraft configurations at the conceptual level. This has motivated the development of a tool which effectively manages the trade-off between high-fidelity levels, flexibility and short turn-around times. This paper presents a CATIA V5-based parametric aircraft geometry modeler developed by Bombardier Aerospace. The aim of the tool is to provide consistent high-fidelity geometric data early in the conceptual aircraft design process. The intended near-term use of the modeler is two-fold: during the early design phase, the modeler computes geometric data such as areas, volumes, ESDU aircraft parameters, etc. In the competitive analysis domain, the tool provides a high-quality three-dimensional model with manageable effort.

The aging of the world population, and call for greater equality in access to public environments has led to an increase in design for persons with reduced mobility (PRM). There are numerous physical and operational constraints and parameters to overcome when designing a successful and marketable PRM environment. Each program evaluates what is to be considered reasonable based on these guidelines (cost, weight, manufacturability, airframe curvature, footprint required, regulations, and usability). However, there are other less tangible parameters to address. For example, what level of dignity or level of privacy does the PRM environment allow? Does the design require additional assistance to access, or can those who are able make independent use of the environment? Most aircraft manufacturers and design entities have recognized the need to improve accessibility aboard single aisle commercial aircraft (Airbus 320 family, Boeing 737, Embraer 190, Bombardier CSERIES).

This paper discusses the correlation of IVHM (Integrated Vehicle Health Management) as an emerging aerospace discipline and the Big Data paradigm widely discussed in the Information Technology industry. The 4-V model is discussed to qualify a Big Data problem in terms of the volume, variety, velocity and veracity of the data involved. Big Data management allows, for example, correlations to be found to “spot business trends, determine quality of research, prevent diseases, combat crime, and determine real-time roadway traffic conditions”. Examining these two fields side by side is necessary and desirable because innovation is very likely to occur when and where different but correlated domains interface. This paper compares the most significant technical components required for Big Data Analytics and IVHM to work.