Plasma models, contribution matrix for detector setup and generated projections for plasma emissivity reconstruction in fusion devices - Open Research Data - Bridge of Knowledge

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Plasma models, contribution matrix for detector setup and generated projections for plasma emissivity reconstruction in fusion devices

Description

The original plasma models for fusion devices, together with the complementary detector setup in the form of a contribution matrix and generated projections. Samples are packed inside a Plasma Tomography Format (PTF) files which is a part of the Plasma Tomography in Fusion Devices Python package, and inside the general JSON format. The constructed dataset consists of 4500 modeled plasma distributions of 60x60 pixels. Reconstructed plasma emissivity distributions were serialized using NumPy Python library. Detector configuration consists of 84 channels gathering line of sight data, with regions of high and low observation density.

Illustration of the publication

Complementary samples from the datasets. Left:  random sample containing modeled twin gaussian plasma emissivity distributions. Right: the same plasma distribution, but obtained by performing a reconstruction using the Minimum Fisher Information method using a projection generated from the modeled distribution.

Dataset file

plasma models for fusion devices.zip
400.8 MB, S3 ETag 766dce161033550bebcfaa0047dc5c9e-1, downloads: 74
The file hash is calculated from the formula
hexmd5(md5(part1)+md5(part2)+...)-{parts_count} where a single part of the file is 512 MB in size.

Example script for calculation:
https://github.com/antespi/s3md5
download file plasma models for fusion devices.zip

File details

License:
Creative Commons: by 4.0 open in new tab
CC BY
Attribution
Software:
Plasma Tomography in Fusion Devices

Details

Year of publication:
2023
Verification date:
2023-02-28
Dataset language:
English
Fields of science:
  • physical sciences (Natural sciences)
  • information and communication technology (Engineering and Technology)
DOI:
DOI ID 10.34808/j0bf-rs65 open in new tab
Funding:
Verified by:
Gdańsk University of Technology

Keywords

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