Combined electric power system and High-Altitude Electromagnetic Pulse (HEMP) models are being developed to determine the effect of a HEMP on the US power grid. The work relies primarily on deterministic methods; however, it is computationally untenable to evaluate the E1 HEMP response of large numbers of grid components distributed across a large interconnection. Further, the deterministic assessment of these components' failures are largely unachievable. E1 HEMP laboratory testing of the components is accomplished, but is expensive, leaving few data points to construct failure models of grid components exposed to E1 HEMP. The use of Bayesian priors, developed using the subject matter expertise, combined with the minimal test data in a Bayesian inference process, provides the basis for the development of more robust and cost-effective statistical component failure models. These can be used with minimal computational burden in a simulation environment such as sampling of Cumulative Distribution Functions (CDFs).

翻译：目前正在开发电力系统与高空电磁脉冲（HEMP）的综合模型，以确定HEMP对美国电网的影响。该工作主要依赖确定性方法；然而，评估分布在大型互联电网中大量电网元件对E1 HEMP的响应，在计算上是不可行的。此外，对这些元件失效的确定性评估在很大程度上也无法实现。虽然已经完成了元件的E1 HEMP实验室测试，但成本高昂，导致可用于构建暴露于E1 HEMP的电网元件失效模型的数据点极少。利用领域专业知识建立的贝叶斯先验，结合贝叶斯推断过程中的少量测试数据，为开发更稳健且更具成本效益的统计元件失效模型提供了基础。这些模型可在仿真环境中（例如对累积分布函数（CDF）进行采样）以最小的计算负担使用。