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A Methodology to Manage System-level Uncertainty During Conceptual Design

机译:在概念设计过程中管理系统级不确定性的方法

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摘要

Current design decisions must be made while considering uncertainty in both models of the design and inputs to the design. In most cases, high fidelity models are used with the assumption that the resulting model uncertainties are insignificant to the decision making process. This paper presents a methodology for managing uncertainty during system-level conceptual design of complex multidisciplinary systems. This methodology is based upon quantifying the information available in a set of observations of computationally expensive subsystem models with more computationally efficient kriging models. By using kriging models, the computational expense of a Monte Carlo simulation to assess the impact of the sources of uncertainty on system-level performance parameters becomes tractable. The use of a kriging model as an approximation to an original computer model introduces model uncertainty, which is included as part of the methodology. The methodology is demonstrated as a decision-making tool for the design of a satellite system.
机译:在考虑设计模型和设计输入的不确定性时,必须做出当前的设计决策。在大多数情况下,使用高保真模型,并假设结果模型的不确定性对决策过程不重要。本文提出了一种在复杂的多学科系统的系统级概念设计过程中管理不确定性的方法。该方法基于量化具有较高计算克里金模型的昂贵计算子系统模型的观测值中的可用信息。通过使用克里金模型,蒙特卡洛模拟评估不确定性来源对系统级性能参数的影响的计算费用变得易于处理。使用克里金模型作为原始计算机模型的近似值会引入模型不确定性,这是方法学的一部分。该方法论被证明是设计卫星系统的决策工具。

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