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.

The work presented in this paper explores several concepts related to the design of complex engineering products and emphasizes on the effects of considering Multidisciplinary Design Optimization (MDO) in the development process. This paper is by no means a comprehensive literature review, but instead, the aim is to discuss some key points through theory and references to common MDO applications. In this respect, the central topics which are addressed herein are the enhancement of the generic product development process, the road towards a better integration of the organization’s functions, the methods to manage complex system architectures, and finally, the shortcomings of the MDO field. As a link to more tangible industrial applications, Unmanned Aerial Vehicles (UAVs) are chosen as an illustrative example due to their technical complexity as well as the demanding requirements of the corresponding market. Overall, the paper shows that despite the current state-of-the-art limitations, MDO can be a valuable tool within the “traditional” design process that has the potential to enable products of better quality while simultaneously reducing the total development time and effort.

This paper presents a Multidisciplinary Design Optimization (MDO) framework that is intended to be employed in the early design stages of Unmanned Aerial Vehicles (UAVs) when the primary focus is on the tradeoffs between the mission, stealth, and surveillance performance requirements. The proposed MDO framework takes into account the aircraft’s geometry, the aerodynamics, the trim, the stability, and the simulation of the mission, but it also includes two additional models for computing the Radar Cross Section (RCS) and the sensor performance. A multi-level solution architecture is implemented in order to tackle the increased complexity of the problem, and it is shown that this type of decomposition can be a more efficient optimization approach compared to the traditional single-level formulation. The operation of the framework is evaluated through single objective optimizations by using the weighted sum method, while it is also investigated whether or not metamodels can be a viable alternative to the computationally expensive RCS and sensor analysis models. Overall, the results show that the mission, stealth, and surveillance performance are conflicting objectives, and therefore, their concurrent consideration in an optimization framework can help increase the available knowledge early on in the design of UAV applications.

This paper presents a multidisciplinary design optimization framework applied to the development of unmanned aerial vehicles with a focus on radar signature and sensor performance requirements while simultaneously considering the flight trajectory. The primary emphasis herein is on the integration and development of analysis models for the calculation of the radar cross section and sensor detection probability, whereas traditional aeronautical disciplines such as aerodynamics and mission simulation are also taken into account in order to ensure a flyable concept. Furthermore, this work explores the effect of implementing trajectory constraints as a supplementary input to the multidisciplinary design optimization process and presents a method that enables the optimization of the aircraft under a three-dimensional flight scenario. To cope with the additional computational cost of the high-fidelity radar cross section and sensor calculations, the use of metamodels is also investigated and an efficient development methodology that can provide high-accuracy approximations for this particular problem is proposed. Overall, the operation and performance of the framework are evaluated against five surveillance scenarios, and the obtained results show that the implementation of trajectory constraints in the optimization has the potential to yield better designs by 12–25% when compared to the more “traditional” problem formulations.

This paper presents a data management and visualization tool that was developed in parallel with a Multidisciplinary Design Optimization (MDO) framework in order to enable a more effective use of the obtained results within the Product Development Process (PDP). To this date, the main problem is that the majority of MDO case studies conclude by suggesting a small number of optimal configurations, which do not really hold any meaningful value for the decision makers since they represent only a narrow area of the design space. In this light, the proposed tool aims to provide designers with new possibilities in respect to post-processing of large data sets, and subsequently, to allow the non-technical teams to be engaged and benefit from the use of MDO in the company practices. As an example, an Unmanned Aerial Vehicle (UAV) configurator developed by using the Graphical User Interface (GUI) of MATLAB is herein presented, and it is shown that a tool for handling the results can be the logical next step towards integrating MDO in the manufacturing industry. Overall, this work aims to demonstrate the benefits of the present visualization and management tool as a complementary addition to an existing optimization framework, and also to determine if this approach can be the right strategy towards improving the MDO method for an eventual use in the PDP of complex pro-ducts like UAVs.

This paper explores the use of Multidisciplinary Design Optimization (MDO) in the development of Unmanned Aerial Vehicles (UAVs) when the requirements include a collaboration in a System of Systems (SoS) environment. In this work, the framework considers models that can capture the mission, stealth, and surveillance performance of each aircraft, while at the same time, a dedicated simulation module assesses the total cooperation effect on a given operational scenario. The resulting mixed continuous and integer variable problem is decomposed with a multi-level architecture, and in particular, it is treated as a fleet allocation problem that includes a nested optimization routine for sizing a “yet-to-be-designed” aircraft. Overall, the models and the framework are evaluated through a series of optimization runs, and the obtained Pareto front is compared with the results from a traditional aircraft mission planning method in order to illustrate the benefits of this SoS approach in the design of UAVs.