OMFIT (One Modeling Framework for Integrated Tasks) is a new software package developed to support integrated modeling and experimental planning. The main idea at the base of OMFIT is to treat files, data and scripts as a uniform collection of objects organized into a tree structure. The OMFIT framework provides a consistent way to access and manipulate such collection of heterogeneous objects, independent of their origin. Within the OMFIT tree, data can be copied or referred from one node to another and tasks can call each other allowing for complex compound task to be built. Such uniform structure allows the definition of a single top-level Graphical User Interface (GUI), to manage tree objects, carry out simulations and analyze the data interactively. OMFIT has the ability to understand many scientific data format. When a file is loaded into OMFIT, its data populates the OMFIT tree, automatically endowing it with many potential uses. Furthermore, integration with MDS+ tree allows direct manipulation of the experimental data. In OMFIT modeling tasks are organized into modules, which can be easily combined to create arbitrarily large multi-physics simulations. Modules inter-dependencies are defined by referencing variables among them. The current version of OMFIT includes modules for magnetic, MSE and kinetic constrained equilibrium reconstruction (EFIT), transport (ONETWO), stability (PEST3) and ray-tracing (GENRAY) analysis. Creation of new modules and customization of existing ones is encouraged and simplified by the availability of high level Python Application Programmer Interfaces (APIs) for the execution of codes on remote servers and creation of application specific GUIs. Visualization of experimental and modeling data is possible within OMFIT, for both quick analysis and publication. More info can be found at https://fusion.gat.com/theory/OMFIT.
A new capability has been implemented in the TGYRO code that uses a single global GYRO simulation (rather than multiple parallel local GYRO radial instances) to calculate flux-matching transport solution plasma density and temperature profiles. This capability will allow for more efficient calculations of global gyrokinetic predictions of transport solution profiles and gradients, and their comparisons to local simulation predictions and experimental results. To facilitate such comparisons, a significant amount of the existing TGYRO code base structure and methodology was retained, with TGYRO flux profiles binned onto a small number of discrete radii analogous to the local approach. These comparisons are essential for quantifying the effects of nonlocality, profile variation, and other finite rho-star effects on transport levels and stiffness, particularly in H-mode plasmas with low, near-marginal transport levels and (relatively) large rho-star. Future work will aim at identifying optimal algorithms for use with the global simulations, and incorporation of momentum transport and turbulent energy exchange terms.
The toroidal radiation asymmetry has been calculated for NIMROD massive gas injection (MGI) simulations, which indicate that a factor of two toroidal variation in radiated power can occur even with a perfectly symmetric source of impurities at the edge. The number and location of injection ports for the ITER disruption mitigation system (DMS) will be decided in 2013, and will be chosen, in part, with the goal of maintaining toroidal radiation asymmetry below acceptable levels. The variation is due to the role of nonaxisymmetric modes in mixing the impurities from the edge to the core, so that be core impurity distribution is asymmetric. This finding suggests that a lower bound for radiation symmetry (with MGI) may exist regardless of the number of toroidal ports.
A driver for the Fokker-Planck code CQL3D was developed and implemented within the IMFIT framework, enabling integrated simulations using CQL3D with the transport module ONETWO, and the RF wave heating and current drive modules, GENRAY and TORAY. The driver accepts two arguments, RFMODEL and RFCODE, set in a configuration file. RFMODEL can be set to one of ‘LH’, ‘EC’, or ‘IC’ to select lower hybrid, electron cyclotron, or ion cyclotron waves respectively. Three corresponding template input files for CQL3D, are also set up in a template directory. The parameter RFCODE, determines whether the configuration file reads plasma profiles and other necessary information from NetCDF output files produced by GENRAY (RFCODE = ‘GENRAY’) or TORAY (RFCODE = ‘TORAY’), and also updates the namelist input variables in the CQL3D input file accordingly. Testing of the CQL3D driver in the IMFIT framework reproduces identical results to those produced from standalone CQL3D simulations.
These highlights are reports of research work in progress and are accordingly subject to change or modification