The fuel ion densities of tritium (T) and deuterium (D) are important parameters for reactor control in fusion experiments. The fuel ion densities typically need to be determined for a wide range of experimental conditions, anywhere between pure deuterium plasmas with trace amounts of T to pure tritium plasmas with trace amounts of D. Given the significantly larger cross section for fusion reactions, compared to or , introducing small amounts of tritium to a deuterium plasma (or vice versa) quickly has a large impact on the neutron emission rates and the neutron energy spectrum. For experiments that use the neutron emission rate as a figure of merit, or for simulations, the time-resolved T and D densities often need to be considered. In this paper, we present a method for determining the densities using multiple neutron diagnostics together with simulations of supra-thermal fuel ions utilizing the plasma transport code TRANSP. The method is set up utilizing a Bayesian framework to estimate the most likely distribution of T and D densities given the available data and the modeled slowing-down ion velocity distribution, using the synthetic neutron diagnostics code DRESS to calculate the expected neutron emission for the given fuel ion distributions. The method is applied to experiments conducted at the JET tokamak, involving deuterium-dominated plasmas with tritium concentrations ranging from 0 to 10%, heated by D neutral beam injection and ion cyclotron resonance frequency heating.
This paper presents a method to determine the densities of deuterium (D) and tritium (T) fuel ions in fusion experiments using multiple neutron diagnostics and plasma transport simulations. The technique estimates the most likely distribution of D and T densities based on neutron emission data and modeled ion velocity distributions. This is crucial for fusion reactor control and understanding the impact of fuel ion composition on neutron production.