Complex engineering systems require integration of simulation of sub-systems and calculation of metrics to drive design decisions. This paper introduces a methodology for designing computational or physical experiments for system-level uncertainty mitigation purposes. The methodology follows a previously determined problem ontology, where physical, functional and modeling architectures are decided upon. By carrying out sensitivity analysis techniques utilizing system-level tools, critical epistemic uncertainties can be identified. Afterwards, a framework is introduced to design specific computational and physical experimentation for generating new knowledge about parameters, and for uncertainty mitigation. The methodology is demonstrated through a case study on an early-stage design Blended-Wing-Body (BWB) aircraft concept, showcasing how aerostructures analyses can be leveraged for mitigating system-level uncertainty, by computer experiments or guiding physical experimentation. The proposed methodology is versatile enough to tackle uncertainty management across various design challenges, highlighting the potential for more risk-informed design processes.

通过计算实验和物理实验，应用敏感性分析技术对复杂工程系统进行不确定性管理，从而减轻系统级不确定性并帮助风险评估设计过程。

识别物理或计算实验条件的方法论以减少不确定性