EFD-C(13)03/16 TRANSP Tests of TGLF and Predictions for ITER

Gyro kinetic simulations of turbulence capture some of the features observed in transport, fluctuations, and correlations measured in tokamak plasmas. These codes calculations are CPU intensive, and are not practical for incorporation in present time-dependant transport codes, so reduced models based on these gyro kinetic codes are being used. An example is the TGLF model which is a quasilinear gyrofluid model calibrated to nonlinear results from the GYRO code. Recently TGLF has been incorporated into TRANSP. Analysis of experimental data using TRANSP with such models provides fundamental understanding of turbulent transport. Predictions of ITER performance with various plasma scenarios using such models are useful for optimizing design and for exposing issues that can be addressed in present experiments and theory. For instance, which combinations of heating, torquing, and current drive are optimal. Another application is for nuclear licensing (e.g. system integrity, neutron rates). Others are generating inputs for design of diagnostic systems and for theoretical studies. An example of the later is Alfvén Eigenmode and AE-induced loss of fast ions. The beam ion distribution can either enhance or reduce the alpha pressure drive of the AE instability. The AE instability can cause dangerous amounts of fast ion losses, as was seen in TFTR. The TRANSP code is being used for self-consistent predictive modeling for ITER. The time evolution of profiles of temperatures and toroidal rotation ! have been predicted assuming boundary values using the GLF23 model. Time-dependent simulations are needed to study efficient startup, safe shutdown, and transients such as magnetic diffusion, sawteeth, and ash accumulation. A new solver PT-SOLVER has been added to TRANSP for stiff transport models. It incorporates TGLF, which includes more physics than does GLF23, but which is much more challenging numerically. Benchmarking and testing of this solver have been reported. Recently this solver is being used to predict densities, temperatures, and angular momentum. For predicting ITER prior to experimental results all of the fields need to be predicted. Here new results verifying, validating, and predicting using PTSOLVER are presented.