Abstract
In helical systems, neoclassical transport is one of the important issues in addition to anomalous transport, because of a strong temperature dependency of heat conductivity and an important role in the radial electric field determination. Therefore, the development of a reliable tool for the neoclassical transport analysis is necessary for the transport analysis in Large Helical Device (LHD). We have developed a neoclassical transport database for LHD plasmas, DCOM/NNW, where mono-energetic diffusion coefficients are evaluated by the Monte Carlo method, and the diffusion coefficient database is constructed by a neural network technique. The input parameters of the database are the collision frequency, radial electric field, minor radius, and configuration parameters (Raxis, beta value, etc). In this paper, database construction including the plasma beta is investigated. A relatively large Shafranov shift occurs in the finite beta LHD plasma, and the magnetic field configuration becomes complex leading to rapid increase in the number of the Fourier modes in Boozer coordinates. DCOM/NNW can evaluate neoclassical transport accurately even in such a configuration with a large number of Fourier modes. The developed DCOM/NNW database is applied to a finite-beta LHD plasma, and the plasma parameter dependences of neoclassical transport coefficients and the ambipolar radial electric field are investigated.
