Jupyter notebooks for neutron radiography data processing and analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Neutron radiography and computed tomography encompass a vibrant range of scientific applications, requiring advanced technique development and cutting-edge data processing and analysis software. We have developed an extensive portfolio of Python-based Jupyter notebooks that are custom-made for a specific experiment and sample geometry. These notebooks do not require any programming skills, although the code is accessible to programming experts if they wish to modify it. The notebooks are available on our analysis servers where the imaging data is also stored, preventing unnecessary and lengthy data transfer. This manuscript gives an overview of our efforts to empower the research community, that uses both the Spallation Neutron Source and High Flux Isotope Reactor imaging capabilities, to process and analyze their data in collaboration with our imaging team.

Original languageEnglish
Title of host publicationNeutron Radiography - 11th World Conference on Neutron Radiography, WCNR 2018
EditorsFilomena Salvemini, Joseph J. Bevitt
PublisherAssociation of American Publishers
Pages198-204
Number of pages7
ISBN (Print)9781644900567
DOIs
StatePublished - 2020
Event11th World Conference on Neutron Radiography, WCNR 2018 - Sydney, Australia
Duration: Sep 2 2018Sep 7 2018

Publication series

NameMaterials Research Proceedings
Volume15
ISSN (Print)2474-3941
ISSN (Electronic)2474-395X

Conference

Conference11th World Conference on Neutron Radiography, WCNR 2018
Country/TerritoryAustralia
CitySydney
Period09/2/1809/7/18

Funding

This manuscript has been authored [or, co-authored] by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). The authors would like to thank Prof. Ed Perfect and his team for their valuable input in improving our research community experience using the Jupyter notebooks. This research used resources at the High Flux Isotope Reactor and Spallation Neutron Source, DOE Office of Science User Facilities operated by the Oak Ridge National Laboratory. This manuscript has been authored [or, co-authored] by UT-Battelle, LLC, under contract DEAC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

  • Analysis
  • Imaging
  • Jupyter
  • Neutron
  • Normalization
  • Notebooks
  • Python

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