**1. Introduction**

The conceptual design of novel aerospace vehicles is usually based on the assessment of initially suggested configurations. Such an approach often implies the consideration of a limited number of initial ideas resulting from earlier designer experience or collective multidisciplinary brainstorming [1]. When designing new aircraft generations however, one should acknowledge that the optimal solution integrating certain disruptive technologies may be left out of scope [2]. Furthermore, one should consider that an early concept fixation reduces the room for later design adjustments, also associated with additional costs [1,3]. However, the certain choice of an optimal concept can be assured by parametric optimization and a detailed analysis of each alternative. This approach is not feasible for novel technologies lacking test data.

The mentioned challenges indicate the necessity for (a) the systematic generation of a larger number of concepts and (b) an efficient and robust approach to assess and compare alternative configurations of complex systems such as aerospace vehicles without relying on quantitative data, especially when such is not available (yet).

These are key focal aspects of the Advanced Morphological Approach (AMA) by Rakov and Bardenhagen [3]. It aims to structure a complex design problem in an intuitive

**Citation:** Todorov, V.T.; Rakov, D.; Bardenhagen, A. Structured Expert Judgment Elicitation in Conceptual Aircraft Design. *Aerospace* **2023**, *10*, 287. https://doi.org/10.3390/ aerospace10030287

Academic Editors: Spiros Pantelakis, Andreas Strohmayer and Jordi Pons-Prats

Received: 3 February 2023 Revised: 4 March 2023 Accepted: 7 March 2023 Published: 14 March 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

way and generate an exhaustive and consistent solution space [3]. In order to replace lacking test data of innovative components, the method intents to lean on the professional opinion of dedicated experts, who would be required to assess the technological alternatives. These evaluations will be used as a scientific basis for the qualitative evaluations and the generation of a wider solution space. The resulting exhaustive solution space allows the consideration of solutions possibly let out of scope during conventional idea generation. By clustering the solutions, the designer is able to identify sub-groups of similar, especially advantageous configurations. These optimal sub-spaces could be then defined as the search boundaries within parametric optimization with Multidisciplinary Aircraft Optimization (MDAO). In other words, the AMA aids to find the optimal design sub-spaces for further investigation with MDAO.

In order to define the AMA as a structured and robust method for conceptual design in aerospace (and complex engineering products in general), the implemented techniques should be carefully studied and justified. For this reason, the enhancement of the initial AMA represents a multi-stage project, visualized in Figure 1. The first stage was dedicated to the definition of the objectives and benefits of the AMA, the overview of other work using the MA in Aerospace, as well as the AMA positioning in the scientific context, presented in Reference [2]. Then, the problem structuring, uncertainty modeling and the main data flow was establishes in the next stage, shown in Reference [4]. The current project stage (the third stage in the figure) focuses on the use of expert opinions as a scientific basis for the qualitative assessment of innovative technologies lacking test data. This context is covered by the current paper which aims to integrate structured expert judgment elicitation (SEJE) methods in pre-conceptual aircraft design and its application in the form of an expert workshop on a wing morphing use case. A deeper solution space analysis, integration of technology interaction aspects, verification, and validation of the "full-scale" methodology (fourth and fifth stage) remain subjects of future work.

In this context, it is first necessary to give a brief overview of the AMA method and define the concrete objectives of the current paper.

**AMA enhancement steps**

**Figure 1.** Main AMA enhancement stages.
