A new technique for tokamak edge density measurement based on microwave interferometer

TL;DR

This paper introduces MILS, a microwave interferometry technique for edge plasma density measurement in tokamaks, supported by a 3D model and a genetic algorithm for accurate density profile reconstruction.

Contribution

The paper presents a novel diagnostic method, MILS, combining a 3D wave propagation model and a genetic algorithm for precise edge plasma density measurement in tokamaks.

Findings

MILS can measure densities from ~10^15 to 10^19 m^-3.

Reconstruction error is approximately 5-15% for densities above 10^17 m^-3.

The method is adaptable to various plasma conditions.

Abstract

Novel approach for density measurements at the edge of a hot plasma device is presented - Microwave Interferometer in the Limiter Shadow (MILS). The diagnostic technique is based on measuring the change in phase and power of a microwave beam passing tangentially through the edge plasma. The wave propagation involves varying combinations of refraction, phase change and further interference of the beam fractions. A 3D model is constructed as a synthetic diagnostic for MILS and allows exploring this broad range of wave propagation regimes. The diagnostic parameters, such as its dimensions, frequency and configuration of the emitter and receiver antennas, should be balanced to meet the target range and location of measurements. It can be therefore adjusted for various conditions and here the diagnostic concept is evaluated on a chosen example, which was taken as suitable to cover densities of ~10^15-10^19 m^-3 on the edge of the ASDEX Upgrade tokamak. Based on a density profile with fixed radial shape, appropriate for experimental density approximation, a database of syntethic diagnostic measurements is built. The developed genetic algorithm genMILS of density profile reconstruction using the constructed database results in quite low numerical error. It is estimated as ~ 5-15 % for density >10^17 m^-3. Therefore, the new diagnostic technique (with dedicated data processing algorithm) has a large potential in practical applications in a wide range of densities, with low numerical error, so the total error and the density estimation accuracy is expected to be defined by experimental uncertainties.