Maximum Likelihood Estimation of diffusion and convection in tokamaks using infinite domains

Abstract

A new method to identify the spatial dependent parameters describing the heat transport, i.e. diffusion and convection, in fusion reactors is presented. These parameters determine the performance of fusion reactors. The method is based on local transfer functions, which are defined between two measurement locations. Estimation of the local transfer functions results in a model of the spatial dependent diffusion and convection. The parameters of the local transfer functions are estimated using Maximum Likelihood Estimation in the frequency domain. This is necessary, because both measurements (input and output of the transfer function) contain noise. Moreover, confidence bounds and validation tests can be used in this framework. Finally, experimental results are presented, which show that the diffusion and convection can be estimated. In this case, the uncertainty bounds are too large on the convection to conclude its presence.