用于非线性MHD模拟的JOREK-STARWALL模块化，包括电阻墙（EUROfusion高级支持团队项目报告JORSTAR/JORSTAR2）
Parallelization of JOREK-STARWALL for non-linear MHD simulations including resistive walls (Report of the EUROfusion High Level Support Team Projects JORSTAR/JORSTAR2)
摘要：
托卡马克装置内的大尺度等离子体不稳定性会受到传导容器壁中流动的电流的影响。这涉及到非线性等离子体动力学及其与壁电流的相互作用。为了研究这个问题，求解磁流体动力学（MHD）方程的代码，称为JOREK [Huysmans G.T.A.和Czarny O. NF 47，659（2007）; Czarny O.和Huysmans G. JCP 227，7423（2008）]，偶联[Hoelzl M.，Journal of Physics：Conference Series，401，012010（2012）]，其具有用于真空区域的模型和名为STARWALL的电阻性导电结构[Merkel P.，Strumberger E.，arXiv：150804911（2015）]。JOREK-STARWALL模型已经应用于执行垂直位移事件（VDE）、电阻壁模式（RWM）、静态H模式和垂直反冲ELM触发的模拟。在项目开始时，由于STARWALL和JOREK中相应的耦合例程消耗大量内存和挂钟时间，无法解决具有大量有限元三角形的实际墙壁结构。此外，STARWALL代码和JOREK耦合例程都仅通过OpenMP部分并行化。该项目的目的是实现MPI并行化，以减少内存消耗和执行时间，使大分辨率的模拟成为可能。
英文摘要：
Large scale plasma instabilities inside a tokamak can be influenced by the currents flowing in the conducting vessel wall. This involves non linear plasma dynamics and its interaction with the wall current. In order to study this problem the code that solves the magneto-hydrodynamic (MHD) equations, called JOREK [Huysmans G.T.A. and Czarny O. NF 47, 659 (2007); Czarny O. and Huysmans G. JCP 227, 7423 (2008)], was coupled [Hoelzl M., et al. Journal of Physics: Conference Series, 401, 012010 (2012)] with the model for the vacuum region and the resistive conducting structure named STARWALL [Merkel P., Strumberger E., arXiv:150804911 (2015)]. The JOREK-STARWALL model has been already applied to perform simulations of Vertical Displacement Events (VDEs), Resistive Wall Modes (RWMs), Quiescent H-Mode, and vertical kick ELM triggering. At the beginning of the project it was not possible to resolve the realistic wall structure with a large number of finite element triangles due to the huge consumption of memory and wall clock time by STARWALL and the corresponding coupling routine in JOREK. Moreover, both the STARWALL code and the JOREK coupling routine were only partially parallelized via OpenMP. The aim of this project is to implement an MPI parallelization to reduce memory consumption and execution time such that simulations with large resolutions become possible.
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