One modeling framework for integrated tasks (OMFIT) is a comprehensive integrated modeling framework which has been developed to enable physics codes to interact in complicated workflows, and support scientists at all stages of the modeling cycle. The OMFIT development follows a unique bottom-up approach, where the framework design and capabilities organically evolve to support progressive integration of the components that are required to accomplish physics goals of increasing complexity. OMFIT provides a workflow for easily generating full kinetic equilibrium reconstructions that are constrained by magnetic and motional Stark effect measurements, and kinetic profile information that includes fast-ion pressure modeled by a transport code. It was found that magnetic measurements can be used to quantify the amount of anomalous fast-ion diffusion that is present in DIII-D discharges, and provide an estimate that is consistent with what would be needed for transport simulations to match the measured neutron rates. OMFIT was used to streamline edge-stability analyses, and evaluate the effect of resonant magnetic perturbation (RMP) on the pedestal stability, which have been found to be consistent with the experimental observations. The development of a five-dimensional numerical fluid model for estimating the effects of the interaction between magnetohydrodynamic (MHD) and microturbulence, and its systematic verification against analytic models was also supported by the framework. OMFIT was used for optimizing an innovative high-harmonic fast wave system proposed for DIII-D. For a parallel refractive index > ∥ n 3, the conditions for strong electron-Landau damping were found to be independent of launched ∥ n and poloidal angle. OMFIT has been the platform of choice for developing a neural-network based approach to efficiently perform a non-linear multivariate regression of local transport fluxes as a function of local dimensionless parameters. Transport predictions for thousands of DIII-D discharges showed excellent agreement with the power balance calculations across the whole plasma radius and over a broad range of operating Nuclear Fusion

Plasma discharges with negative triangularity (δ = −0.4) shape have been created in the DIII-D tokamak with significant normalized beta (βN = 2.7) and confinement characteristic of the high confinement mode (H98y2 = 1.2) despite the absence of an edge pressure pedestal and no edge localized modes (ELMs). These inner-wall-limited plasmas have similar global performance as a positive triangularity (δ = +0.4) ELMing H-mode discharge with the same plasma current, elongation and cross-sectional area. For cases both of dominant electron cyclotron heating with Te/Ti > 1 and dominant neutral beam injection heating with Te/Ti = 1, turbulent fluctuations over radii 0.5 < ρ < 0.9 were reduced by 10-50% in the negative triangularity shape compared to the matching positive triangularity shape, depending on radius and conditions.

Recent EAST/DIII-D joint experiments on the high poloidal beta tokamak regime in DIII-D have demonstrated fully noninductive operation with an internal transport barrier (ITB) at large minor radius, at normalized fusion performance increased by ⩾30% relative to earlier work (Politzer et al 2005 Nucl. Fusion 45 417). The advancement was enabled by improved understanding of the 'relaxation oscillations', previously attributed to repetitive ITB collapses, and of the fast ion behavior in this regime. It was found that the 'relaxation oscillations' are coupled core-edge modes amenable to wall-stabilization, and that fast ion losses which previously dictated a large plasma-wall separation to avoid wall over-heating, can be reduced to classical levels with sufficient plasma density. By using optimized waveforms of the plasma-wall separation and plasma density, fully noninductive plasmas have been sustained for long durations with excellent energy confinement quality, bootstrap fraction ⩾80%, β ⩽ 4 N , β ⩾ 3 P , and β ⩾ % 2 T . These results bolster the applicability of the high poloidal beta tokamak regime toward the realization of a steady-state fusion reactor.

Robust validation of predictive turbulent transport models requires quantitative comparisons to experimental measurements at multiple levels, over a range of physically relevant conditions. Toward this end, a series of carefully designed validation experiments has been performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)] to obtain comprehensive multifield, multipoint, multiwavenumber fluctuation measurements and their scalings with key dimensionless parameters. The results of two representative validation studies are presented: an elongation scaling study performed in beam heated L-mode discharges and an electron heating power scan performed in quiescent H-mode (QH-mode) discharges. A 50% increase in the elongation j is observed to lead to a $50% increase in energy confinement time s e and accompanying decrease in fluctuation levels, qualitatively consistent with a priori theoretical predictions and nonlinear GYRO [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] simulations. However, these simulations exhibit clear quantitative differences from experiment in the predicted magnitudes and trends with radius of turbulent fluxes and fluctuation levels which cannot be fully accounted for by uncertainties due to transport stiffness. In the QH-mode study, local nonlinear GYRO simulations that neglect fast ion effects show a similar proportional response to the applied electron cyclotron heating as the experiment, but overpredict the magnitudes of transport and fluctuation levels by a factor of 10 or more. Possible sources of this overprediction, namely nonlocal effects and self-consistent fast beam ions, are identified and discussed. V

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflow that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. The NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.