Simulation Uncertainty in Multidisciplinary Design

多学科设计中的仿真不确定性

• 批准号: 9812857
• 负责人: John Renaud
• 金额: $ 41.68万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-01 至 2003-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9812857&HistoricalAwards=false
• 关键词: Simulation; Uncertainty; Multidisciplinary; Design

This grant provides funding for the development of a decision based design framework for the design of complex engineering systems such as automobiles, aircraft or consumer products. The design of these engineering systems involves extensive use of computer simulation design tools. Each computer simulation model is an abstraction of reality and has some uncertainty associated with its performance predictions. This research will investigate how these uncertainties propagate through a multidisciplinary system comprised of many discipline-specific simulation tools. A goal of this research is to be able to quantify these propagated uncertainties for use in a decision-based design framework. This investigation will evaluate techniques available from experimental data analysis for estimating the worst case propagated uncertainty in complex engineering systems and investigate the utility of performing Monte Carlo simulations on response surface approximations of system performance for quantifying the distributions of the propagated uncertainties. Having quantified propagated uncertainties in complex systems, the second phase of this research effort will be devoted to the implementation of a decision-based design framework. An optimization algorithm based on a trust region managed augmented Lagrangian approach for concurrent subspace design/optimization will be used to drive the decision-based design framework. This optimization will be based on artificial neural network response surface approximations of the system performance. The optimizer will maximize the expected utility of the net revenue for the total life cycle cost of the product subject to stochastic performance constraints. It is anticipated that the results of this research will lead to improved product performances as well as reduced product development times at reduced cost and risk. The development of a decision-based design framework will demonstrate that designers can effectively manage both the uncertainty and risk associated with the simulation based design of new products.

该赠款为开发基于决策的设计框架提供资金，用于设计复杂的工程系统，例如汽车、飞机或消费品。 这些工程系统的设计涉及计算机模拟设计工具的广泛使用。 每个计算机仿真模型都是现实的抽象，并且具有与其性能预测相关的一些不确定性。 这项研究将调查这些不确定性如何通过由许多特定学科模拟工具组成的多学科系统传播。 这项研究的目标是能够量化这些传播的不确定性，以便在基于决策的设计框架中使用。 这项研究将评估实验数据分析中可用于估计复杂工程系统中最坏情况传播不确定性的技术，并研究对系统性能的响应面近似执行蒙特卡罗模拟以量化传播不确定性分布的效用。 在量化了复杂系统中传播的不确定性后，这项研究工作的第二阶段将致力于实施基于决策的设计框架。 基于用于并发子空间设计/优化的信任域管理增强拉格朗日方法的优化算法将用于驱动基于决策的设计框架。 这种优化将基于系统性能的人工神经网络响应面近似。 优化器将最大化受随机性能约束的产品总生命周期成本的净收入的预期效用。 预计这项研究的结果将提高产品性能，缩短产品开发时间，降低成本和风险。 基于决策的设计框架的开发将证明设计人员可以有效地管理与新产品的基于仿真的设计相关的不确定性和风险。