This paper presents a framework to support decision-making in aircraft conceptual design optimisation under uncertainty. Emphasis is given to graphical visualisation methods capable of providing holistic yet intuitive relationships between design, objectives, feasibility and uncertainty spaces. Two concepts are introduced to allow interactive exploration of the effects of (1) target probability of constraint satisfaction (price of feasibility robustness) and (2) uncertainty reduction through increased state-of-knowledge (cost of uncertainty) on design and objective spaces. These processes are tailored to handle multi-objective optimisation problems and leverage visualisation techniques for dynamic inter-space mapping. An information reuse strategy is presented to enable obtaining multiple robust Pareto sets at an affordable computational cost. A case study demonstrates how the presented framework addresses some of the challenges and opportunities regarding the adoption of Uncertainty-based Multidisciplinary Design Optimisation (UMDO) in the aerospace industry, such as design margins policy, systematic and conscious definition of target robustness and uncertainty reduction experiments selection and prioritisation.

中文翻译：

---

不确定性下飞机概念设计优化中增强决策的框架

本文提出了一个框架来支持不确定性下飞机概念设计优化的决策。重点是能够在设计、目标、可行性和不确定性空间之间提供整体而直观的关系的图形可视化方法。引入了两个概念，以允许交互式探索（1）约束满足的目标概率（可行性稳健性的价格）和（2）通过增加设计和目标空间的知识状态（不确定性成本）来减少不确定性的影响。这些过程专门用于处理多目标优化问题并利用可视化技术进行动态空间间映射。提出了一种信息重用策略，以能够以可承受的计算成本获得多个稳健的帕累托集。