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Radial anomalous diffusion coefficients are among the largest sources of uncertainty in mean‐field plasma‐edge codes such as SOLPS‐ITER. These coefficients are machine, scenario, and space‐dependent, thus hampering the predictive and interpretive capability of these codes. In fact, modellers usually adjust these coefficients manually, based on expert judgement or on large, computationally expensive, parameter scans. Matching data from various diagnostics, each with their own experimental uncertainties, additionally complicates the problem of finding a good parameter set. In addition, standard non‐linear regression techniques have shown to become prohibitive for expensive plasma‐edge simulations with many unknown parameters, as gradient calculation was based on finite differences. In this paper, we apply algorithmic differentiation (AD) as an efficient and more accurate alternative for gradient calculation in large, continuously developed codes as SOLPS‐ITER. In addition, the lack of uncertainty information and danger of data overfitting, key limitations of regression techniques, are overcome by combining data and uncertainties from different diagnostics in a Bayesian framework. We implement for the first time such a Bayesian inference framework into SOLPS‐ITER, using gradient‐based optimization with gradients obtained through tangent AD to find the maximum a posteriori (MAP) values of the parameters. The recently developed κ turbulence model is employed to limit the number of unknown parameters compared to full spatial profiles of diffusion coefficients. The Bayesian MAP‐estimation is compared to standard regression techniques on a small‐scale tokamak. We adopt fictitious experimental data obtained from a reference SOLPS‐ITER solution with artificial measurement noise. [ABSTRACT FROM AUTHOR]

The predictive capabilities of mean‐field plasma edge transport codes are significantly reduced by the empirically determined radial diffusion coefficients commonly used to account for the turbulent transport. This paper aims to assess a two‐equation model including both turbulent kinetic energy and turbulent enstrophy for an improved description of the mean‐field turbulent transport. A turbulent enstrophy equation is analytically derived for isothermal, electrostatic, two‐dimensional, interchange‐dominated ExB turbulence in the scrape‐off layer. Evaluation of this equation shows that interchange is the dominant source, while the sheath loss and viscous terms provide the main sinks of turbulent enstrophy. Transport effects turn out to be of minor importance. A model for the combined turbulent kinetic energy and enstrophy equations and the particle transport is constructed starting from a one‐equation model for the turbulent kinetic energy. The resulting two‐equation model is shown to retain the dominant dynamics of the latter while improving its scalings. [ABSTRACT FROM AUTHOR]

Mean‐field plasma edge transport codes such as SOLPS‐ITER heavily rely on ad‐hoc radial diffusion coefficients to approximately model anomalous transport. Such coefficients are experimentally determined and vary between different machines, and also depend on the operational regime and plasma location within the same device. Therefore, to match experimental data the modeller is required to manually tune several free parameters in expensive simulations, and the code's predictive capabilities are significantly downgraded. As a solution, a new model has been developed for SOLPS‐ITER, solving an additional transport equation for the turbulent kinetic energy k, derived by consistently time‐averaging the Braginskii equations, and including a diffusive closure for the anomalous particle flux. This closure model relates the anomalous diffusion coefficient to the local k value. The resulting equation structure and its closure are inspired by TOKAM2D isothermal interchange turbulence simulation results. Within this model, fewer and hopefully more universal free parameters are retained, thus improving the code's predictive capabilities. The new model has been tested on a COMPASS case for which upstream plasma profiles were available. Experimental data and a reference solution, obtained by matching the profiles through manual tuning of radial diffusivities, have been used to estimate the parameters of our new transport model. A ballooned particle diffusivity profile is retrieved by the new radial transport model, thanks to the proposed interchange drive. The obtained upstream profiles qualitatively agree with the experiment and prove the new model is a promising first attempt to be further refined. [ABSTRACT FROM AUTHOR]