A week-long OMFIT developers code-camp was held November 11-15 at General Atomics. This was the sixth code camp and it accomplished several important objectives. Some highlights include the implementation of a procedure for consistently obtaining equilibrium reconstructions with low Grad Shafranov error from EFIT, which is a critical requirement for accurate MHD stability calculations. Also, a python implementation of the SAT0 and SAT1 TGLF saturation models has been made available and will form the basis for a project aimed at improving how linear turbulent growth rates are translated into transport fluxes. A prototype for multithreaded version of the OMFIT GUI has also been developed with promising initial results. Finally, the group addressed numerous issues related to the transition of OMFIT from Python 2 to Python 3. With over 300,000 lines of code this is not easy feat, and testing under the new Python 3 environment will continue. A new automated regression system, which was further refined at the code-camp, has been a key element in supporting this effort. A tutorial on the topic of regression testing was recorded and made available on the OMFIT documentation website, and is hosted on the https://omfit.io domain.

New analysis shows that microtearing modes (MTMs) are the dominant electron energy transport mechanism in the large-radius internal transport barrier region, where ion transport has been reduced to neoclassical levels, of high beta poloidal discharges in DIII-D. Extensive linear gyrokinetic simulations performed with the CGYRO code find that conventional local drift-wave and ballooning instabilities in this region are fully stabilized by the large local Shafranov shift (“alpha-stabilization”), whereas the MTMs are destabilized at large values of alpha. Moreover, nonlinear simulations indicate that the MTMs are able to drive electron energy transport levels consistent with experimentally inferred levels. Consistent with the tearing nature of the instability, and also contrary to drift and ballooning modes, the MTM growth rates and transport levels are found to be most sensitive to magnetic shear rather than pressure gradients. The results were presented at the 2019 APS-DPP meeting by UCSD postdoctoral researcher X. Jian, and have been accepted for publication in Physical Review Letters.