In a previous work that investigated atomic collisional-radiative models, Boltzmann grouping was implemented to reduce and accelerate detailed-configuration-accounting or DCA-based CR simulations, exhibiting distinct advantages over other CR reduction techniques. However, the selection of level groups under this reduction technique was manually performed and required several iterations to construct the appropriate groups that properly showed the advantages associated with Boltzmann grouping. Therefore, a clustering technique was implemented to automatically group detailed (LS-coupled) atomic states with limited user interference. Clustering in conjunction with the Boltzmann grouping technique were applied to collisional and coronal simulations in this work to demonstrate the feasibility of automatic level grouping techniques to produce accurate reduced simulations under various plasma conditions.

在以前的研究原子碰撞辐射模型的工作中，玻尔兹曼分组的实施是为了减少和加速详细配置会计或基于DCA的CR模拟，与其他CR减少技术相比，它具有明显的优势。但是，在此归约技术下手动选择级别组，需要进行几次迭代才能构建适当的组，以正确显示与玻尔兹曼分组有关的优点。因此，实现了一种聚类技术，可以在有限的用户干扰下自动对详细的（LS耦合）原子状态进行分组。