
Daniel Kennedy developed robust data ingestion capabilities for the pyro-kinetics/pyrokinetics repository, focusing on ELITEINP equilibrium and kinetics modeling from .eqin files. He implemented an inline equilibrium reader with 2D psi(R,Z) interpolation and improved error handling and unit consistency, leveraging Python and scientific computing techniques. His work extended the kinetics reader to support impurity-aware plasma species by parsing charge, mass, and density, enhancing the fidelity of plasma simulations. By integrating backend development, data parsing, and numerical analysis, Daniel’s contributions improved data reliability and simulation readiness, enabling more accurate equilibrium and kinetics modeling for plasma physics research and design.
July 2025 — Pyrokinetics: Delivered ELITEINP data ingestion capabilities to support robust equilibrium and kinetics modeling from .eqin formats. Implemented an inline .eqin reader, 2D psi(R,Z) interpolation, and improved error handling and unit consistency. Expanded kinetics reader to include impurities (charge, mass, density) for plasmas, enabling impurity-aware species construction. The work improves data reliability, accelerates simulation readiness, and enhances modeling fidelity for design and analysis.
July 2025 — Pyrokinetics: Delivered ELITEINP data ingestion capabilities to support robust equilibrium and kinetics modeling from .eqin formats. Implemented an inline .eqin reader, 2D psi(R,Z) interpolation, and improved error handling and unit consistency. Expanded kinetics reader to include impurities (charge, mass, density) for plasmas, enabling impurity-aware species construction. The work improves data reliability, accelerates simulation readiness, and enhances modeling fidelity for design and analysis.

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