Improved prediction scheme for ion heat turbulent transport
Physics of Plasmas(2022)
摘要
A novel scheme to predict the turbulent transport of ion heat of magnetic confined plasmas is developed by combining mathematical optimization techniques employed in data analysis approaches and first-principle gyrokinetic simulations. Gyrokinetic simulation, as a first-principle approach, is a reliable way to predict turbulent transport. However, in terms of the flux-matching [Candy et al., Phys. Plasmas 16, 060704 (2009)], quantitative transport estimates by gyrokinetic simulations incur extremely heavy computational costs. In order to reduce the costs of quantitative transport prediction based on the gyrokinetic simulations, we develop a scheme with the aid of a reduced transport model. In the scheme, optimization techniques are applied to find relevant input parameters for nonlinear gyrokinetic simulations, which should be performed to obtain relevant transport fluxes and to optimize the reduced transport model for a target plasma. The developed scheme can reduce the numbers of the gyrokinetic simulations to perform the quantitative estimate of the turbulent transport levels and plasma profiles. Utilizing the scheme, the predictions for the turbulent transport can be realized by performing the first-principle simulations once for each radial position. Published under an exclusive license by AIP Publishing.
更多查看译文
关键词
turbulent transport,prediction heat,improved prediction scheme
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要