Louis Lamérand, Didier Auroux, Philippe Ghendrih, Francesca Rapetti, Eric Serre
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引用次数: 0
Abstract
Two-dimensional transport codes for the simulation of tokamak plasma are reduced version of full 3D fluid models where plasma turbulence has been smoothed out by averaging. One of the main issues nowadays in such reduced models is the accurate modelling of transverse transport fluxes resulting from the averaging of stresses due to fluctuations. Transverse fluxes are assumed driven by local gradients, and characterised by ad hoc diffusion coefficients (turbulent eddy viscosity), adjusted by hand in order to match numerical solutions with experimental measurements. However, these coefficients vary substantially depending on the machine used, type of experiment and even the location inside the device, reducing drastically the predictive capabilities of these codes for a new configuration. To mitigate this issue, we recently proposed an innovative path for fusion plasma simulations by adding two supplementary transport equations to the mean-flow system for turbulence characteristic variables (here the turbulent kinetic energy k and its dissipation rate \(\epsilon \)) to estimate the turbulent eddy viscosity. The remaining free parameters are more driven by the underlying transport physics and hence vary much less between machines and between locations in the plasma. In this paper, as a proof of concept, we explore, on the basis of digital twin experiments, the efficiency of the assimilation of data to fix these free parameters involved in the transverse turbulent transport models in the set of averaged equations in 2D.
用于模拟托卡马克等离子体的二维传输代码是全三维流体模型的缩小版,其中等离子体湍流已通过平均化得到平滑。目前,这种简化模型的主要问题之一是如何准确模拟波动应力平均化产生的横向传输通量。横向通量被假定为由局部梯度驱动,并以临时扩散系数(湍流涡流粘度)为特征,通过人工调整使数值解法与实验测量结果相匹配。然而,这些系数因所使用的机器、实验类型甚至设备内部位置的不同而有很大差异,从而大大降低了这些代码对新配置的预测能力。为了缓解这一问题,我们最近为聚变等离子体模拟提出了一条创新之路,即在湍流特征变量(此处为湍流动能 k 及其耗散率 \(\epsilon \))的均流系统中添加两个补充传输方程,以估算湍流涡流粘度。其余自由参数更多地受到底层输运物理的驱动,因此在不同机器和等离子体不同位置之间的变化要小得多。在本文中,作为概念验证,我们在数字孪生实验的基础上,探索了数据同化的效率,以固定二维平均方程组中横向湍流输运模型所涉及的这些自由参数。
期刊介绍:
Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis.
This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.