To simulate multispecies impurity transport in tokamaks, a set of coupled continuity equations including source and sink terms from atomic processes (rate terms) were solved numerically. The diffusion and rate terms are integrated separately in time using a fractional step-splitting technique which is accurate to second order in the time step. Calculations were performed treating individually all the ionization stages of oxygen and iron impurities in a hydrogen plasma. Calculated O VI and O VII relative density profiles agree qualitatively with profiles measured in the Adiabatic Toroidal Compressor (ATC) tokamak when purely neoclassical diffusion coefficients are used.

Understanding impurity transport in the core of tokamak plasmas is central to achieving controlled fusion. Indeed impurities are ubiquitous in these devices and their presence in the core are detrimental to plasma confinement (fuel dilution, Bremsstrahlung). Recently, specific attention was given to the convective mechanism related to the gradient of the toroidal rotation to explain experimental flat/hollow impurity profiles in the plasma core. In this thesis, up-to-date modelling tools (NEO for neoclassical transport and GKW for turbulent transport) including the impact of toroidal rotation are used to study both the neoclassical and turbulent contributions to impurity fluxes. A comparison of the experimental and modelled carbon density peaking factor (R/LnC) is performed for a large number of baseline and hybrid H-mode plasmas (increased confinement regimes) with modest to high toroidal rotation from the European tokamak JET. Confrontation of experimental and modelled carbon peaking factor yields two main results. First roto-diffusion is found to have a nonnegligible impact on the carbon peaking factor at high values of the toroidal rotation frequency gradient. Second, there is a tendency to overpredict the experimental R/LnC in the core inner region where the carbon density profiles are hollow. This disagreement between experimental and modelled R/LnC, closely related to the collisionality, is also observed for the momentum transport channel which hints at a common parallel symmetry breaking mechanism lacking in the simulations.

Impurity transport is an issue of utmost importance for tokamaks. Indeed high-Z materials are only partially ionized in the plasma core, so that they can lead to prohibitive radiative losses even at low concentrations, and impact dramatically plasma performance and stability. On-axis accumulation of tungsten has been widely observed in tokamaks.While the very core impurity peaking is generally attributed to neoclassical effects, turbulent transport could well dominate in the gradient region at ITER relevant collisionality. Up to recently, first principles simulations of corresponding fluxes were performed with different dedicated codes, implicitly assuming that both transport channels are separable and therefore additive. The validity of this assumption is questionned. Simulations obtained with the gyrokinetic code GYSELA have shown clear evidences of a neoclassical-turbulence synergy for impurity transport and allowed the identification of a mechanism that underly this synergy.An analytical work allows to compute the level and the structure of the axisymmetric part of the electric potential knowing the turbulence intensity. Two mechanisms are found for the generation of poloidal asymmetries of the electric potential: flow compressibility and the ballooning of the turbulence. A new prediction for the neoclassical impurity flux in presence of large poloidal asymmetries and pressure anisotropies has been derived. A fair agreement has been found between the new theoretical prediction for neoclassical impurity flux and the results of a GYSELA simulation displaying large poloidal asymmetries and pressure anisotropies induced by the presence of turbulence.

This thesis presents two new techniques for analyzing data from impurity transport experiments in magnetically confined plasmas, with specific applications to the Alcator C-Mod tokamak. The objective in developing these new techniques is to improve the quality of the experimental results used to test simulations of turbulent transport: better characterization of the uncertainty in the experimental results will yield a better test of the simulations. Transport codes are highly sensitive to the gradients of the background temperature and density profiles, so the first half of this thesis presents a new approach to fitting tokamak profiles using nonstationary Gaussian process regression. This powerful technique overcomes many of the shortcomings of previous spline-based data smoothing techniques, and can even handle more complicated cases such as line-integrated measurements, computation of second derivatives, and 2d fitting of spatially- and temporally-resolved measurements. The second half of this thesis focuses on experimental measurements of impurity transport coefficients. It is shown that there are considerable shortcomings in existing point estimates of these quantities. Next, a linearized model of impurity transport data is constructed and used to estimate diagnostic requirements for impurity transport measurements. It is found that spatial resolution is more important than temporal resolution. Finally, a fully Bayesian approach to inferring experimental impurity transport coefficient profiles which overcomes the shortcomings of the previous approaches through use of multimodal nested sampling is developed and benchmarked using synthetic data. These tests reveal that uncertainties in the transport coefficient profiles previously attributed to uncertainties in the temperature and density profiles are in fact entirely explained by changes in the spline knot positions. Appendices are provided describing the extensive work done to determine the derivatives of stationary and nonstationary covariance kernels and the open source software developed as part of this thesis work. The techniques developed here will enable more rigorous benchmarking of turbulent transport simulations, with the ultimate goal of developing a predictive capability.

A Monte-Carlo Impurity (MCI) transport code is used to follow trace impurities through multiple ionization states in realistic 2-D tokamak geometries. The MCI code is used to study impurity transport along the open magnetic field lines of the Scrape-off Layer (SOL) and to understand how impurities get into the core from the SOL. An MCI study concentrating on the entrainment of carbon impurities ions by deuterium background plasma into the DIII-D divertor is discussed. MCI simulation results are compared to experimental DIII-D carbon measurements.