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DisruptionPy References¤

Here follows a non-exhaustive list of projects, publications, and conference contributions that leveraged or referenced DisruptionPy.

Projects¤

  • C Rea, et al. (2023), "Open and FAIR Fusion for Machine Learning Applications", Project website.

Publications¤

  • AR Saperstein, et al. (2025), "Design and development of an off-normal warning system for SPARC", Nucl. Fusion 65 116007, DOI: 10.1088/1741-4326/ae074e
  • GL Trevisan, et al. (2025), "DisruptionPy: An open-source physics-based scientific framework for disruption analysis of fusion plasmas", JOSS, under review
  • L Spangher, et al. (2025), "DisruptionBench and Complimentary New Models: Two Advancements in Machine Learning Driven Disruption Prediction", J. Fusion. Energ. 44 26, DOI: 10.1007/s10894-025-00495-2
  • J Stillerman, et al. (2025), "MDSplusML: Optimizations for data access to facilitate machine learning pipelines", Fus. Eng. Des. 211 114770, DOI: 10.1016/j.fusengdes.2024.114770
  • AD Maris, et al. (2024), "Correlation of the L-mode density limit with edge collisionality", Nucl. Fusion 65 016051, DOI: 10.1088/1741-4326/ad90f0
  • GL Trevisan, et al. (2024), "DisruptionPy: An open-source physics-based scientific framework for disruption analysis of fusion plasmas", Zenodo, DOI: 10.5281/zenodo.13935223
  • Z Keith, et al. (2024), "Risk-aware framework development for disruption prediction: Alcator C-Mod and DIII-D survival analysis", J. Fusion. Energ. 43 21, DOI: 10.1007/s10894-024-00413-y

Conferences¤

  • 67th APS-DPP Meeting (2025)
  • AD Maris, et al. (2025), "Collisionality scaling of the tokamak density limit: data-driven analysis, cross-device prediction, and real-time avoidance" BO04.5
  • Z Keith, et al. (2025), "Enabling data-driven NTM studies with advanced mode labeling", BP13.167
  • C Rea, et al. (2025), "Research in support of the SPARC Off-Normal Warning System", JO04.9
  • AR Saperstein, et al. (2025), "Validation of simulated radiative collapse events in TORAX", NP13.161
  • H Wietfeldt, et al. (2025), "Characterization of UFOs on Alcator C-Mod and WEST to inform SPARC operation" NP13.163
  • EdD Zapata-Cornejo, et al. (2025), "Time series classification algorithms for confinement regime identification in C-Mod" NP13.169

  • GL Trevisan, et al. (2025), "A large-scale automated EFIT recomputation workflow for disruption studies at 1 kHz", PP13.93

  • 6th International Conference on Data-Driven Plasma Science (2025)

  • Z Keith, et al. (2025), "A tearing mode database for Alcator C-Mod and DIII-D"

  • Y Wei, et al. (2025), "DisruptionPy: An open-source physics-based scientific package for disruption studies on magnetic fusion experiment devices"

  • 45th ITPA-MDC Meeting (2025)

  • AD Maris, et al. (2025), "Cross-device prediction and real-time avoidance of the density limit"
  • AR Saperstein, et al. (2025), "Progress on the development of an off-normal warning system for SPARC"

  • H Wietfeldt, et al. (2025), "Characterizing UFO Disruptions on Alcator C-Mod"

  • 3rd AI for Fusion CRP (2025)

  • C Rea, et al. (2025), "Open and FAIR Fusion for Machine Learning Applications"

  • Open Source Software for Fusion Energy (2025)

  • Y Wei, et al. (2025), "DisruptionPy: an open-source Python library for disruption study.", POS-10

  • 66th APS-DPP Meeting (2024)

  • AD Maris, et al. (2024), "Correlation of the tokamak density limit with edge collisionality", BI02.2
  • H Wietfeldt, et al. (2024), "Discerning Why Some High-Z UFOs in C-Mod Caused Immediate Disruptions while Others Did Not", NP12.111
  • GL Trevisan, et al. (2024), "Functional Improvements and Technical Developments of a Community-driven and Physics-informed Numerical Library for Disruption Studies", PP12.9
  • Y Wei, et al. (2024), "Physics validation of parameter methods in DisruptionPy", PP12.10
  • C Rea, et al. (2024), "Open and FAIR Fusion for Machine Learning Applications", PP12.27

  • AR Saperstein, et al. (2024), "Development and preliminary calibration of an off-normal warning system for SPARC", TO06.9

  • 3rd IAEA Technical Meeting on Plasma Disruptions and their Mitigation (2024)

  • AD Maris, et al. (2024), "Correlation of the tokamak density limit with edge collisionality", 32301

  • AR Saperstein, et al. (2024), "Development and preliminary calibration of an off-normal warning system for SPARC", 32305

  • 65th APS-DPP Meeting (2023)

  • A Maris, et al. (2023), "Data-driven tokamak density limit boundary identification", BP11.108
  • L Spangher, et al. (2023), "Do Fusion Plasma Time-Series Have a Persistent Memory that Machine Learning May Exploit?", JP11.121
  • AR Saperstein, et al. (2023), "Off-normal warning threshold development on SPARC", JP11.123
  • Z Keith, et al. (2023), "Risk-aware framework development for disruption prediction: Alcator C-Mod survival analysis", JP11.124