The present study introduces an automated multidisciplinary optimization (MDO) workflow that, for the first time, couples an explicit dynamic bird strike analysis with a post-impact static stress check. This joint problem is solved during preliminary wing sizing by integrating batch Bayesian optimization on Kriging surrogates with a variance-based variable screening procedure. The optimization problem comprises 19 thickness design variables and two highly non-linear constraints, imposing a maximum leading edge penetration and a maximum post-impact front spar stress while minimizing wing mass. The workflow is demonstrated on a five-bay metallic wing segment, yielding a 43% weight saving over the best-performing design during initial data generation while respecting CS 25.631 crashworthiness limits. Results demonstrated substantial computational savings by variable screening and highlighted the necessity of the stress constraint, as designs satisfying only the penetration depth requirement could still experience critical post-impact stress levels.

Most MDO problems currently do not include manufacturing as an optimization domain. Within the H2020 project AGILE 4.0 the intent is to bring manufacturing into the MDO domain using MBSE techniques developed within the project. To demonstrate how manufacturing can be brought into the MDO domain application cases are set up that resemble MDO problems from industry. In this paper, the MDO techniques will be used for the design of a Flap for a regional jet. The manufacturing aspect is represented by including the manufacturing cost of the flap in a Design Of Experiments (DOE). In this DOE different flap kinematic mechanisms and different flap sizes and paths are explored. The DOE is set up using the MDO toolset developed within AGILE 4.0. It allows for an automatic definition of the DOE workflow. The DOE results show that the choice of flap configuration has a significant effect on the Flap manufacturing cost, the flap wright and the landing performance of the aircraft. Next steps will be to investigate more flap configurations, improved the manufacturing cost model used and to set up a true flap optimization.

According to a study performed by the Project Management Institute, around 47% of unsuccessful projects do not meet their goals and objectives due to poor requirements management. Taking requirements into account during the aircraft design process and ensuring requirement compliance during all design phases is important to obtain good and feasible aircraft designs. However, a typical aircraft design process is very complex and many requirements need to be taken into account. This paper proposes a new framework that implements requirements in the design process by establishing a direct link between Model-Based Systems Engineering and Multidisciplinary Design Analysis and Optimization (MDAO). Model-based requirements are directly implemented in the optimization problem and based on the requirement verification methods the MDAO workflows are formulated. When requirements or verification methods change, the workflow is automatically updated accordingly. This way, requirement compliance can either be automatically enforced or checked based on the optimization or analysis results. Automatically generated requirement reports provide information on the requirement compliance results. The framework has been implemented in a software prototype, which was applied to the design of a wing box, showing the functionalities of the framework. With the framework, the traceability from requirements to product design is improved, as all stakeholders can see how the design process was formulated and how requirement compliance has been achieved. Furthermore, optimized designs can be obtained that satisfy all the stakeholders' needs.