
Daniel Burgess developed core features for the OpenFUSIONToolkit/JPEC repository, focusing on equilibrium modeling and MHD stability analysis for plasma physics applications. He implemented an end-to-end workflow that reconstructs plasma states using Soloviev analytical equilibrium integration, leveraging Julia and Fortran for backend development and data parsing. Daniel introduced Mercier stability analysis tooling with spline interpolation and visualization, improving local stability assessments and debugging through Jupyter notebooks. He also enhanced project structure and benchmarking reproducibility by updating data files and reorganizing the repository. His work demonstrated depth in scientific computing, numerical methods, and full stack development, supporting robust research workflows.
December 2025 — OpenFUSIONToolkit/JPEC: Key structural improvements and benchmarking data updates to boost onboarding, reproducibility, and performance testing. Delivered a clarified project layout, a default equilibrium file, and refreshed benchmarking data, setting the stage for reliable benchmarking and faster integration for downstream teams.
December 2025 — OpenFUSIONToolkit/JPEC: Key structural improvements and benchmarking data updates to boost onboarding, reproducibility, and performance testing. Delivered a clarified project layout, a default equilibrium file, and refreshed benchmarking data, setting the stage for reliable benchmarking and faster integration for downstream teams.
July 2025 performance summary for OpenFUSIONToolkit/JPEC. Focused on delivering an end-to-end equilibrium modeling and stability analysis workflow with robust data handling, visualization, and targeted bug fixes to improve reliability and business value. Key work targeted end-user impact: stronger plasma state reconstruction, more reliable stability assessments, and better decision support through validated visualizations.
July 2025 performance summary for OpenFUSIONToolkit/JPEC. Focused on delivering an end-to-end equilibrium modeling and stability analysis workflow with robust data handling, visualization, and targeted bug fixes to improve reliability and business value. Key work targeted end-user impact: stronger plasma state reconstruction, more reliable stability assessments, and better decision support through validated visualizations.

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