Neutral beam injection into reversed magnetic shear DIII-D and ASDEX Upgrade plasmas produces a variety of Alfvénic activity including toroidicity-induced Alfvén eigenmodes and reversed shear Alfvén eigenmodes (RSAEs). These modes are studied during the discharge current ramp phase when incomplete current penetration results in a high central safety factor and increased drive due to multiple higher order resonances. Scans of injected 80 keV neutral beam power on DIII-D showed a transition from classical to AE dominated fast ion transport and, as previously found, discharges with strong AE activity exhibit a deficit in neutron emission relative to classical predictions. By keeping beam power constant and delaying injection during the current ramp, AE activity was reduced or eliminated and a significant improvement in fast ion confinement observed. Similarly, experiments in ASDEX Upgrade using early 60 keV neutral beam injection drove multiple unstable RSAEs. Periods of strong RSAE activity are accompanied by a large (peak dS n =S n % 60%) neutron deficit. Losses of beam ions modulated at AE frequencies were observed using large bandwidth energy and pitch resolving fast ion loss scintillator detectors and clearly identify their role in the process. Modeling of DIII-D loss measurements using guiding center following codes to track particles in the presence of ideal magnetohydrodynamic (MHD) calculated AE structures (validated by comparison to experiment) is able to reproduce the dominant energy, pitch, and temporal evolution of these losses. While loss of both co and counter current fast ions occurs, simulations show that the dominant loss mechanism observed is the mode induced transition of counter-passing fast ions to lost trapped orbits. Modeling also reproduces a coherent signature of AE induced losses and it was found that these coherent losses scale proportionally with the amplitude; an additional incoherent contribution scales quadratically with the mode amplitude.

Fast ion transport models currently implemented in the tokamak transport code TRANSP (Hawryluk 1980 Physics of Plasmas Close to Thermonuclear Conditions (Brussels: CEC)) are not capturing important aspects of the physics associated with resonant transport caused by instabilities such as toroidal Alfvén eigenmodes (TAEs). This work describes the implementation of a fast ion transport model consistent with the basic mechanisms of resonant mode-particle interaction. The model is formulated in terms of a probability distribution function for the particle's steps in phase space, which is consistent with the Monte Carlo approach used in TRANSP. The proposed model is based on the analysis of the fast ion response to TAE modes through the ORBIT code (White and Chance 1984 Phys. Fluids 27 2455), but it can be generalized to higher frequency modes (e.g. compressional and global Alfvén eigenmodes) and to other numerical codes or theories.

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Alfvénic instabilities (AEs) are well known as a potential cause of enhanced fast ion transport in fusion devices. Given a specific plasma scenario, quantitative predictions of (i) expected unstable AE spectrum and (ii) resulting fast ion transport are required to prevent or mitigate the AEinduced degradation in fusion performance. Reduced models are becoming an attractive tool to analyze existing scenarios as well as for scenario prediction in time-dependent simulations. In this work, a neutral beam heated NSTX discharge is used as reference to illustrate the potential of a reduced fast ion transport model, known as kick model, that has been recently implemented for interpretive and predictive analysis within the framework of the time-dependent tokamak transport code TRANSP. Predictive capabilities for AE stability and saturation amplitude are first assessed, based on given thermal plasma profiles only. Predictions are then compared to experimental results, and the interpretive capabilities of the model further discussed. Overall, the reduced model captures the main properties of the instabilities and associated effects on the fast ion population. Additional information from the actual experiment enables further tuning of the model's parameters to achieve a close match with measurements.