Aircraft Conceptual Design Optimization with Uncertain Contributing Analyses

This paper outlines the development of a multi-disciplinary design optimization (MDO) architecture for aircraft conceptual design that includes the assessment of uncertainties introduced by approximate equations or computational methods in the contributing disciplinary analyses. Aircraft conceptual design traditionally harnesses prior knowledge in the form of empirical or statistical equations and low fidelity analysis. This approach is computationally inexpensive and allows for rapid design iterations. However, the use of approximate methods introduces uncertainties that can lead to an optimum conceptual design that, when subjected to more detailed analysis later in the design process, is found to fail one or more of the design goals. This may lead to costly revision. By assessing the uncertainty of the contributing analyses using Reliability Based Design Optimization (RBDO) methods, the probability of failure of a given conceptual design can be estimated and minimized.