No abstract

Product development, especially in aerospace, has become more and more interconnected with its operational environment. In a constant changing world, the operational environment will be subjected to changes during the life cycle of the product. The operational environment will be affected by not only technical and non-technical perturbations, but also economical, managerial and regulatory decisions, thus requiring a more global product development approach. One way to try tackling such complex and intertwined problem advocates studying the envisioned product or system in the context of system of systems (SoS) engineering. SoSs are all around us, probably in any field of engineering, ranging from integrated transport systems, public infrastructure systems to modern homes equipped with sensors and smart appliances; from cities filling with autonomous vehicle to defence systems.Since also aerospace systems are certainly affected, this work will present a holistic approach to aerospace product development that tries spanning from needs to technology assessment. The proposed approach will be presented and analysed and key enablers and future research directions will be highlighted from an interdisciplinary point of view. Consideration of the surrounding world will require to look beyond classical engineering disciplines.

The aim of this paper is to present the most common practices in multidisciplinary design optimization (MDO) of aerial vehicles over the past decade. The literature sample is identified through established internet search engines, and a stringent review methodology is implemented in order to ensure the selection of the most relevant sources. In this work, the primary emphasis is on the assessment of the state-of-the-art framework development strategies, while at a secondary level, the objective is to identify the possible improvement directions by evaluating the research trends and gaps. As an additional contribution, statistical studies are also provided, and it is shown how MDO of aerial vehicles has evolved in terms of problem formulation, disciplinary modeling, analysis capabilities, tool implementation, and general applicability. Given this foundation as well as the results of the review, this work concludes by presenting a roadmap for guiding academia and industry in respect to the application of MDO on aerial vehicles. Overall, the roadmap together with the literature review is not only expected to serve as a guide for newcomers into the MDO field but also as an elementary basis which will allow researchers to conduct additional studies in this important and constantly evolving area of design.

In this study the use of a high-order panel code within a framework for aircraft concept design is discussed. The framework is intended to be a multidisciplinary optimization tool to be adopted from the very beginning of the conceptual design phase in order to define and refine the aircraft design, with respect to its aerodynamic, stability and control, structure and basic aircraft systems. The presented work is aimed at developing a module for aerodynamic analysis of concepts as a basis for a direct search optimization of the concept layout. The design criterion, used in the example presented here, is to minimize the maximum take-off weight required to fulfil the mission. Classic and simple equations are used together with the data generated by the panel code solver to calculate the aircraft's performances. Weights are calculated by means of statistical group weight equations, but the weight could also be calculated from a CAD-model. The design of an Unmanned Combat Air Vehicle is used as test case for three different optimization algorithms: one gradient method based (Fmincon), one non-gradient based (Complex) and one Genetic Algorithm (GA).Comparison of results and performances shows that the Genetic Algorithm is best fitted for the specific problem, having the by far best hit rate, even if it is at a cost of longer computing time. The Complex algorithm requires less iterations and is also able to find the optimum solution, but with a worse hit rate, while Fmincon can not reach to a global optimum. The suggested optimized configuration for the aircraft is very similar to the Boeing X-45C and Northrop Grumman X-47B. Nomenclature α = angle of attack B = semi wing span C = specific fuel consumption c d0 = parasite drag coefficient= lift coefficient as function of the angle of attack c L,α=0 = lift coefficient at zero angle of attack = maximum allowed effective stress in the internal structure material

The presented work is centered on the evaluation of Micro or Mini Air Vehicles (MAV) that have been automatically designed and manufactured. An in-house developed design framework uses several coupled computer software's to generate the geometric design in CAD, a well as list of off the shelf components for the propulsion system, and computer code for autonomous flight ready to upload in the intended autopilot. The paper describes the experiences made so far regarding automation of the design process and of manufacturing. Furthermore, it presents results from evaluation and analysis of the optimization algorithm and flight testing, and from continuing work with the framework to achieve deeper understanding of the process and to fine-tune the design automation performance. The flight data is correlated to the predicted performances to validate the models and design process.