Bayesian integrated estimation of two-dimensional tungsten concentration profiles at WEST using soft x-ray and bolometry diagnostics

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Tungsten accumulation in the core of tokamak plasmas poses a major risk to the core performance through strong radiative cooling. Reliable estimates of tungsten concentrations are therefore critical towards fusion-relevant operation. In this article, we present Bayesian integrated data analysis (IDA) on measurements from soft x-ray, interferometry and electron cyclotron emission diagnostics at WEST, to jointly estimate the two-dimensional tungsten concentration profiles and kinetic profiles ( n e and T e ). IDA aims at providing reliable parameter estimates that are consistent with all available measurements, together with adequate uncertainty quantification. The IDA approach relies on the exploration of a high-dimensional joint posterior distribution of the quantities of interest, which, in our work, is implemented efficiently via Markov chain Monte Carlo sampling techniques with reparameterization. This method has been tested on both synthetic and experimental data. It yields reliable tungsten concentration estimates in the core plasma, whereas the uncertainty strongly increases towards the edge. Therefore, we also incorporate bolometry measurements, with first results indicating the strong potential of this method.