Data Assimilation System Based On Integrated Transport Simulation Of Large Helical Device Plasma

A data assimilation technique is applied to the integrated transport simulation (TASK3D) of a plasma in Large Helical Device (LHD). We use the ensemble Kalman filter (EnKF) as a data assimilation method for the estimation of state variables composed of the electron and ion temperature, density, numerical coefficients of turbulence models, and NBI heat deposition. The time series data of experimentally measured temperature and density profiles are assimilated into TASK3D. The obtained electron and ion temperature profiles and temporal variations by the data assimilation system agree well with measured ones owing to the optimization of the employed turbulent transport model and the heat deposition. These results indicate the effectiveness and validity of the data assimilation approach for accurate prediction of the behavior of fusion plasmas and the possibility of advanced turbulence modeling.