An Approach for Robust Design of Reactive Power Metal Mixtures Based on Non-deterministic Micro-scale Shock Simulation
An Approach for Robust Design of Reactive Power Metal Mixtures Based on Non-deterministic Micro-scale Shock Simulation
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基于非确定性微尺度冲击仿真的无功功率金属混合物鲁棒设计方法
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
D. Benson
中科院分区：
文献类型：
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作者：
Hae;R. Austin;J. Allen;D. McDowell;F. Mistree;D. Benson
在这篇文章中，我们提出了一种涉及计算密集和选择性随机的过程的材料的稳健设计方法。所考虑的材料体系是由铝和氧化铁(Al+Fe_2O_3)组成的活性颗粒金属混合物(RPMM)。对离散的含能粒子混合物进行了激波模拟，以预测系统的机械和热行为，混合物的设计者将使用这些行为来实现稳健的微尺度反应引发。用于预测材料系统行为的方法是带误差裕度指标的稳健概念探索法(RCEM-EMI)。误差容限指数是一种数学构造，它指示平均系统性能的位置以及考虑设计变量和系统模型的可变性的这种性能的传播。模型响应的可变性可能是由于系统的变化，而系统的变化不能很容易地根据噪声系数进行参数化。此外，由于模拟和实验的成本导致数据的缺乏，导致经验模型中的参数不确定。以计算有效的方式估计经验模型中的系统响应变异性和参数不确定性，以形成误差裕度指数，然后利用该指数搜索范围内的设计规范集合。最后，介绍了RCEM-EMI在RPMM设计中的应用。
In this paper, we propose a method for the robust design of materials involving processes that are computationally intensive and selectively random. The material system considered is a reactive particle metal mixture (RPMM) composed of aluminum and iron oxide (Al+Fe2O3). Shock simulations of discrete energetic particle mixtures are performed to predict the system’s mechanical and thermal behavior that will be used by a designer of the mixture to achieve robust micro-scale reaction initiation. The method used to predict the behavior of the material system is the robust concept exploration method with error margin index (RCEM-EMI). An error margin index is a mathematical construct indicating the location of mean system performance and the spread of this performance considering both variability in design variables and models of the system. Variability in responses of a model may be due to system variation that cannot be easily parameterized in terms of noise factors. Furthermore, lack of data, due to the cost of simulations and experiments, leads to uncertain parameters in empirical models. System response variability and parameter uncertainty in an empirical model are estimated in a computationally efficient manner to formulate the error margin indices, which are then leveraged to search for ranged sets of design specifications. Finally, the RCEM-EMI is illustrated for designing a RPMM.