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An integrated risk analysis methodology in a multidisciplinary design environment.

机译:多学科设计环境中的集成风险分析方法。

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Design of complex, one-of-a-kind systems, such as space transportation systems, is characterized by high uncertainty and, consequently, high risk. It is necessary to account for these uncertainties in the design process to produce systems that are more reliable. Systems designed by including uncertainties and managing them, as well, are more robust and less prone to poor operations as a result of parameter variability.; The quantification, analysis and mitigation of uncertainties are challenging tasks as many systems lack historical data. In such an environment, risk or uncertainty quantification becomes subjective because input data is based on professional judgment. Additionally, there are uncertainties associated with the analysis tools and models. Both the input data and the model uncertainties must be considered for a multi disciplinary systems level risk analysis.; This research synthesizes an integrated approach for developing a method for risk analysis. Expert judgment methodology is employed to quantify external risk. This methodology is then combined with a Latin Hypercube Sampling - Monte Carlo simulation to propagate uncertainties across a multidisciplinary environment for the overall system. Finally, a robust design strategy is employed to mitigate risk during the optimization process. This type of approach to risk analysis is conducive to the examination of quantitative risk factors.; The core of this research methodology is the theoretical framework for uncertainty propagation. The research is divided into three stages or modules. The first two modules include the identification/quantification and propagation of uncertainties. The third module involves the management of uncertainties or response optimization. This final module also incorporates the integration of risk into program decision-making.; The risk analysis methodology, is applied to a launch vehicle conceptual design study at NASA Langley Research Center. The launch vehicle multidisciplinary environment consists of the interface between configuration and sizing analysis outputs and aerodynamic parameter computations. Uncertainties are analyzed for both simulation tools and their associated input parameters. Uncertainties are then propagated across the design environment and a robust design optimization is performed over the range of a critical input parameter.; The results of this research indicate that including uncertainties into design processes may require modification of design constraints previously considered acceptable in deterministic analyses.
机译:复杂的一种系统(例如太空运输系统)的设计具有很高的不确定性,因此风险也很高。为了产生更可靠的系统,有必要在设计过程中考虑这些不确定性。通过包括不确定性并对其进行管理而设计的系统,由于参数的可变性,因此更加健壮,并且不太容易出现不良操作。由于许多系统缺乏历史数据,因此量化,分析和缓解不确定性是一项艰巨的任务。在这种环境下,由于输入数据是基于专业判断的,因此风险或不确定性量化变得很主观。此外,分析工具和模型也存在不确定性。在多学科系统水平的风险分析中,必须考虑输入数据和模型不确定性。这项研究综合了开发风险分析方法的综合方法。采用专家判断方法来量化外部风险。然后,此方法与Latin Hypercube Sampling-Monte Carlo模拟相结合,从而在整个系统的多学科环境中传播不确定性。最后,采用鲁棒的设计策略来减轻优化过程中的风险。这种类型的风险分析方法有助于检查定量风险因素。该研究方法的核心是不确定性传播的理论框架。研究分为三个阶段或模块。前两个模块包括不确定性的识别/量化和传播。第三个模块涉及不确定性的管理或响应优化。该最终模块还将风险整合纳入计划决策中。风险分析方法已应用于NASA兰利研究中心的运载火箭概念设计研究。运载火箭的多学科环境由配置和大小分析输出与空气动力学参数计算之间的接口组成。分析了仿真工具及其相关输入参数的不确定性。然后,不确定性会在整个设计环境中传播,并在关键输入参数的范围内进行可靠的设计优化。这项研究的结果表明,将不确定性纳入设计过程可能需要修改先前在确定性分析中认为可以接受的设计约束。

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