
Marvin Tollnitsch enhanced the sogno-platform/dpsim repository by expanding EMT signal network modeling capabilities, focusing on both technical depth and usability. He developed advanced two-terminal SSN components with full RLC circuit support, integrating them into the C++ codebase and exposing their functionality through Python bindings for broader accessibility. His work included implementing trapezoidal discretization for state-space matrices, improving simulation fidelity and enabling faster experimentation. Marvin also created example circuits and Jupyter notebooks, wiring them into the build and test workflow to ensure reliability. This effort strengthened the platform’s modularity and made high-fidelity EMT simulations more accessible to Python users.
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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