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[REVIEW]: kugelpy: A Python package for modeling pebble bed reactor run-in #7727

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editorialbot opened this issue Jan 27, 2025 · 7 comments
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editorialbot commented Jan 27, 2025

Submitting author: @ethan-fowler (Ethan Fowler)
Repository: https://github.com/idaholab/kugelpy.git
Branch with paper.md (empty if default branch): joss_paper
Version: v0.1.0
Editor: @kellyrowland
Reviewers: @sskutnik, @damar-wicaksono
Archive: Pending

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Markdown: [![status](https://joss.theoj.org/papers/c6c494948f0a7374f1c2782964784404/status.svg)](https://joss.theoj.org/papers/c6c494948f0a7374f1c2782964784404)

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Reviewer instructions & questions

@sskutnik & @damar-wicaksono, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
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The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @kellyrowland know.

Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest

Checklists

📝 Checklist for @sskutnik

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Checking the BibTeX entries failed with the following error:

Failed to parse BibTeX on value "," (COMMA) ["@", #<BibTeX::Entry >, {:title=>["High-fidelity simulations of the run-in process for a pebble-bed reactor"], :author=>["Stewart, Ryan Hunter and Balestra, Paolo and Reger, David and Merzari, Elia and Strydom, Gerhard"], :abstractnote=>["Pebble-bed reactors (PBRs) rely on a continual feed of fuel pebbles being cycled through the core. As a result, they require a “run-in” period in order to reach an equilibrium state. The run-in period for a PBR is a complex, time-dependent problem that requires the injection of new fuel, different types of fuel, and power increases. This complexity in the run-in makes it important to capture the physical processes in order to generate an accurate representation. The present work details the creation of a high-fidelity Monte Carlo methodology for analyzing the run-in and subsequent approach to equilibrium for PBRs. The methodology entails a Python module wrapped around Serpent so as to perform neutronics calculations, move pebbles, refuel the core, and discharge pebbles, thereby modeling the explicit behavior of the PBR run-in. Further, three run-in simulations (a constant temperature profile, a linear temperature profile, and a constant temperature profile using control rods) were examined in order to identify the key physical phenomena present in the run-in process. Utilizing kugelpy, we found the inclusion of a temperature profile to be important for accurately capturing a discharge burnup (around 141 MWd/kg), a consistent k-eff (around 1.005), and an average pebble power (around 2.5 kW/pebble) that all fall within acceptable limits."], :doi=>["10.1016/j.anucene.2023.110193"], :url=>["https://www.osti.gov/biblio/2282751"], :journal=>["Annals of Nuclear Energy"], :issn=>["0306-4549"]}, ",", "number", "="]

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👉📄 Download article proof 📄 View article proof on GitHub 📄 👈

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Software report:

github.com/AlDanial/cloc v 1.98  T=0.09 s (381.2 files/s, 196881.3 lines/s)
--------------------------------------------------------------------------------
Language                      files          blank        comment           code
--------------------------------------------------------------------------------
Text                              2             10              0           9055
Python                           14            568            923           2946
MATLAB                            3            616            216           1756
Markdown                         10            155              0           1145
TeX                               1              5              0             76
YAML                              2              3              5             27
Bourne Again Shell                1              0             18             20
Dockerfile                        1              7              2              9
--------------------------------------------------------------------------------
SUM:                             34           1364           1164          15034
--------------------------------------------------------------------------------

Commit count by author:

    16	Fowler
     3	Wendy Skinner

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Paper file info:

📄 Wordcount for paper.md is 885

✅ The paper includes a Statement of need section

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License info:

✅ License found: BSD 3-Clause "New" or "Revised" License (Valid open source OSI approved license)

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sskutnik commented Jan 28, 2025

Review checklist for @sskutnik

Conflict of interest

  • I confirm that I have read the JOSS conflict of interest (COI) policy and that: I have no COIs with reviewing this work or that any perceived COIs have been waived by JOSS for the purpose of this review.

Code of Conduct

General checks

  • Repository: Is the source code for this software available at the https://github.com/idaholab/kugelpy.git?
  • License: Does the repository contain a plain-text LICENSE or COPYING file with the contents of an OSI approved software license?
  • Contribution and authorship: Has the submitting author (@ethan-fowler) made major contributions to the software? Does the full list of paper authors seem appropriate and complete?
  • Substantial scholarly effort: Does this submission meet the scope eligibility described in the JOSS guidelines
  • Data sharing: If the paper contains original data, data are accessible to the reviewers. If the paper contains no original data, please check this item.
  • Reproducibility: If the paper contains original results, results are entirely reproducible by reviewers. If the paper contains no original results, please check this item.
  • Human and animal research: If the paper contains original data research on humans subjects or animals, does it comply with JOSS's human participants research policy and/or animal research policy? If the paper contains no such data, please check this item.

Functionality

  • Installation: Does installation proceed as outlined in the documentation?
  • Functionality: Have the functional claims of the software been confirmed?
  • Performance: If there are any performance claims of the software, have they been confirmed? (If there are no claims, please check off this item.)

Documentation

  • A statement of need: Do the authors clearly state what problems the software is designed to solve and who the target audience is?
  • Installation instructions: Is there a clearly-stated list of dependencies? Ideally these should be handled with an automated package management solution.
  • Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).
  • Functionality documentation: Is the core functionality of the software documented to a satisfactory level (e.g., API method documentation)?
  • Automated tests: Are there automated tests or manual steps described so that the functionality of the software can be verified?
  • Community guidelines: Are there clear guidelines for third parties wishing to 1. Contribute to the software 2. Report issues or problems with the software 3. Seek support

Software paper

  • Summary: Has a clear description of the high-level functionality and purpose of the software for a diverse, non-specialist audience been provided?
  • A statement of need: Does the paper have a section titled 'Statement of need' that clearly states what problems the software is designed to solve, who the target audience is, and its relation to other work?
  • State of the field: Do the authors describe how this software compares to other commonly-used packages?
  • Quality of writing: Is the paper well written (i.e., it does not require editing for structure, language, or writing quality)?
  • References: Is the list of references complete, and is everything cited appropriately that should be cited (e.g., papers, datasets, software)? Do references in the text use the proper citation syntax?

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