Managing divertor plasmas is crucial for operating reactor scale tokamak devices due to heat and particle flux constraints on the divertor target. Simulation is an important tool to understand and control these plasmas, however, for real-time applications or exhaustive parameter scans only simple approximations are currently fast enough. We address this lack of fast simulators using neural PDE surrogates, data-driven neural network-based surrogate models trained using solutions generated with a classical numerical method. The surrogate approximates a time-stepping operator that evolves the full spatial solution of a reference physics-based model over time. We use DIV1D, a 1D dynamic model of the divertor plasma, as reference model to generate data. DIV1D's domain covers a 1D heat flux tube from the X-point (upstream) to the target. We simulate a realistic TCV divertor plasma with dynamics induced by upstream density ramps and provide an exploratory outlook towards fast transients. State-of-the-art neural PDE surrogates are evaluated in a common framework and extended for properties of the DIV1D data. We evaluate (1) the speed-accuracy trade-off; (2) recreating non-linear behavior; (3) data efficiency; and (4) parameter inter- and extrapolation. Once trained, neural PDE surrogates can faithfully approximate DIV1D's divertor plasma dynamics at sub real-time computation speeds: In the proposed configuration, 2ms of plasma dynamics can be computed in $\approx$0.63ms of wall-clock time, several orders of magnitude faster than DIV1D.

翻译：管理偏滤器等离子体对于反应堆级托卡马克装置的运行至关重要，因为偏滤器靶板存在热流和粒子流约束。模拟是理解和控制这些等离子体的重要工具，然而在实时应用或全面参数扫描中，目前只有简单的近似方法能够满足速度要求。我们通过神经PDE替代模型来解决快速模拟器缺乏的问题——这是基于数据驱动的神经网络替代模型，利用经典数值方法生成的解进行训练。该替代模型逼近一个时间步进算子，该算子可随时间演化参考物理模型的完整空间解。我们采用DIV1D（一种偏滤器等离子体一维动态模型）作为参考模型生成数据。DIV1D的域覆盖从X点（上游）到靶板的1D热流管。我们模拟了由上游密度斜坡驱动的真实TCV偏滤器等离子体动力学，并对快速瞬态过程进行了探索性展望。在统一框架下评估了最先进的神经PDE替代模型，并针对DIV1D数据特性进行了扩展。我们从以下四个方面进行评估：(1) 速度-精度权衡；(2) 非线性行为再现；(3) 数据效率；(4) 参数内插与外推。经训练后，神经PDE替代模型能以亚实时计算速度忠实逼近DIV1D的偏滤器等离子体动力学：在所提配置中，2毫秒的等离子体动力学计算仅需约0.63毫秒的壁钟时间，比DIV1D快数个数量级。