
Worked on the sogno-platform/dpsim repository to expand electromagnetic transient (EMT) signal network modeling, focusing on state-space nodal (SSN) enhancements and Python integration. Developed advanced two-terminal SSN components and full RLC circuit support, implementing trapezoidal discretization for state-space A and B matrices within MathUtils to improve simulation fidelity. Integrated these models into the build system and exposed them through Python bindings, enabling broader experimentation and accessibility. Added example circuits and Jupyter notebooks to demonstrate new features, while refining CMake and header organization for maintainability. Utilized C++, Python, and simulation modeling expertise to deliver a more modular, Python-friendly toolchain.
December 2025 monthly summary for sogno-platform/dpsim focused on expanding EMT SSN modeling capabilities, Python accessibility, and build integration for broader experimentation. Delivered advanced SSN modeling enhancements including two-terminal SSN components, full RLC circuit support, Python bindings, and a suite of example circuits, paired with discretization improvements for state-space A/B matrices. Business value centers on higher-fidelity EMT simulations, faster experimentation, and a more modular, Python-friendly toolchain.
December 2025 monthly summary for sogno-platform/dpsim focused on expanding EMT SSN modeling capabilities, Python accessibility, and build integration for broader experimentation. Delivered advanced SSN modeling enhancements including two-terminal SSN components, full RLC circuit support, Python bindings, and a suite of example circuits, paired with discretization improvements for state-space A/B matrices. Business value centers on higher-fidelity EMT simulations, faster experimentation, and a more modular, Python-friendly toolchain.

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