Structural identifiability and noise-induced rank inflation in mine ventilation resistance inversion — code and numerical results

Published: 16 October 2026| Version 1 | DOI: 10.17632/hfg7924h5z.1
Contributors:
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Description

Code and numerical results supporting the manuscript “Structural identifiability and noise-induced rank inflation in mine ventilation resistance inversion” by Shuchang Zhang and Shaoqi Kong. The archive contains 20 Python files implementing an 18-step computational workflow, five necessary small numerical transcriptions, 56 frozen calculation outputs, six editable table bodies and nine vector figures. It includes exact modular rank certificates, baseline-equivalent resistance counterexamples, experimental design and covariance-processing comparisons, four synthetic topology checks, and verification using an independent nodal formulation. The primary published network is attributed to Wang et al. (2022), https://doi.org/10.1371/journal.pone.0275437. Its public supplementary PDF is retrieved by the workflow rather than redistributed. Additional transcription sources, published inconsistencies, boundary assumptions and model limitations are documented in the archive README and provenance files. No new field measurements were collected. Research support: Shanxi Province Higher Education Science and Technology Innovation Program (2022L055); Shanxi Province Key Research and Development Program, Key Technologies Research and Demonstration for Carbon Peaking and Carbon Neutrality (202402080301013 and 202402080301016); Open Fund of the State Key Laboratory of Coal and Coalbed Methane Co-Mining (2024KF24).

Files

Steps to reproduce

1. Download Reproduction.zip and extract it into a writable directory. Enter the reproduction directory. 2. Install Python and the pinned dependencies: python -m pip install -r requirements.txt 3. Run: python code/run_all.py 4. The 18-step workflow retrieves the primary public source table, reconstructs the network inputs, recalculates all numerical studies, runs the main, nodal and topology checks, and generates the figures and tables. A first run requires internet access; no LaTeX installation is required for numerical reproduction. 5. Compare outputs with the frozen results included in the archive. Run in a working copy because generated outputs are overwritten. If the publisher download is unavailable, obtain the S1 Table from https://doi.org/10.1371/journal.pone.0275437 and save it as data/raw/Topological data.pdf. The expected source PDF SHA256 is 7235c03f4e9d5cdc625b5837182bcceef4bc0c26010f329b93c4f7738ad31bbe. See README.md, data/README.md and research/data_provenance.md for sources, fields and assumptions.

Institutions

Categories

Mining Engineering

Funders

  • Shanxi Province Higher Education Science and Technology Innovation Program
    Grant ID: 2022L055
  • Shanxi Province Key Research and Development Program, Key Technologies Research and Demonstration for Carbon Peaking and Carbon Neutrality
    Grant ID: 202402080301013
  • Shanxi Province Key Research and Development Program, Key Technologies Research and Demonstration for Carbon Peaking and Carbon Neutrality
    Grant ID: 202402080301016
  • Open Fund of the State Key Laboratory of Coal and Coalbed Methane Co-Mining
    Grant ID: 2024KF24

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