A Methodology to Identify Physical or Computational Experiment Conditions for Uncertainty Mitigation

• URL: http://arxiv.org/abs/2405.13931v1
• Date: Wed, 22 May 2024 18:59:42 GMT
• Title: A Methodology to Identify Physical or Computational Experiment Conditions for Uncertainty Mitigation
• Authors: Efe Y. Yarbasi, Dimitri N. Mavris,
• Abstract summary: This paper introduces a methodology for designing computational or physical experiments for system-level uncertainty mitigation purposes. The proposed methodology is versatile enough to tackle uncertainty management across various design challenges.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: 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.

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