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Fusion energy: Progress, partnerships, and the path to deployment
Over the past decade, fusion energy has moved decisively from scientific aspiration toward a credible pathway to a new energy technology. Thanks to long-term federal support, we have significantly advanced our fundamental understanding of plasma physics—the behavior of the superheated gases at the heart of fusion devices. This knowledge will enable the creation and control of fusion fuel under conditions required for future power plants. Our progress is exemplified by breakthroughs at the National Ignition Facility and the Joint European Torus.
Andrew E. Johnson, Dan Kotlyar, Stefano Terlizzi, Gavin Ridley
Nuclear Science and Engineering | Volume 194 | Number 11 | November 2020 | Pages 1016-1024
Technical Paper | doi.org/10.1080/00295639.2020.1723992
Articles are hosted by Taylor and Francis Online.
The serpentTools Python package is presented as a useful and efficient alternative for processing Serpent results. One positive attribute of Serpent is that many output files are exported directly in a MATLAB format, allowing for results to be loaded with minimal to no effort. However, some files for larger analyses may require immense amounts of memory to load and store all the data, leading to long wait times. To expedite the process of data handling and ease common analyses, the Computational Reactor Engineering lab at the Georgia Institute of Technology has released and is maintaining the serpentTools Python package: a set of data parsers and containers intended to streamline analysis with Serpent outputs. The parsers are capable of processing large outputs with ease, and yield all data to the user in a simple object-oriented framework. Data can be read into Python in comparable or better times than MATLAB, with the option to store only data needed for a specific purpose. Furthermore, common analyses are implemented directly into the package to expedite frequent analysis, including plotting meshed data and flux specta. serpentTools is designed to be a useful and practical manner by which the Serpent community can load and analyze data inside a Python environment. This paper presents the Python package, highlighting some basic features, and compares capabilities to similar platforms.