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Using designer confidence and a dynamic Monte Carlo simulation tool to evaluate uncertainty in system models

机译:使用设计者信心和动态蒙特卡罗模拟工具来评估系统模型中的不确定性

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摘要

As the use of distributed engineering models becomes more prevalent, engineers need tools to evaluate the quality of these models and understand how subsystem uncertainty affects predictions of system behavior. This thesis develops a tool that enables designers and engineers to specify their perceptions of confidence. These data are then translated into appropriate probability distributions. Monte-Carlo-based methods are used to automatically provide correct propagation of these distributions within an integrated modeling environment. A case study using an assembly tolerance problem is shown and different confidence modeling methods are compared. The methods benchmarked are: worst case; statistical; conventional Monte Carlo simulation; and the dynamic Monte Carlo tool developed in this thesis. Finally the dynamic Monte Carlo tool is used together with surrogate modeling techniques. Comparisons based on implementation time, model execution time, and robustness are provided.
机译:随着分布式工程模型的使用越来越普遍,工程师需要工具来评估这些模型的质量,并了解子系统的不确定性如何影响系统行为的预测。本文开发了一种工具,使设计人员和工程师可以指定他们的自信心。然后将这些数据转换为适当的概率分布。基于蒙特卡洛的方法用于在集成建模环境中自动提供这些分布的正确传播。显示了使用装配公差问题的案例研究,并比较了不同的置信度建模方法。基准测试的方法是:最坏的情况;统计;传统的蒙特卡洛模拟;以及本文开发的动态蒙特卡洛工具。最后,将动态蒙特卡洛工具与替代建模技术一起使用。提供了基于实现时间,模型执行时间和鲁棒性的比较。

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