
Over a three-month period, contributed to EvoEngine by developing advanced simulation features focused on ecological and physics-based realism. Work included implementing fungus and rot propagation using C++ and compute shaders, optimizing data storage and visualization for large-scale simulations, and refining propagation mechanics for nuanced environmental interactions. Enhanced the dynamic strand subsystem with crack pattern modeling, moisture parameter improvements, and collision handling optimizations, leveraging GLSL and GPU programming to increase stability and performance. Expanded tree dynamics with adaptive settings, multi-species support, and leaf health metrics, addressing core stability issues and enabling broader experimentation for data-driven forest simulation scenarios.
Summary of 2026-01 for EvoEngine (edisonlee0212/EvoEngine): Implemented advanced tree dynamics with adaptive settings and multi-tree support (Elm, Oak, Spruce), including rot–moisture interaction, leaf health metrics, and fungus competition dynamics. Added leaf drop mechanics and strengthened structural integrity evaluation through improved moisture handling. Expanded parameterization and logging to enable broader experimentation across Elm, Oak, and Spruce configurations. Fixed a core stability issue related to internal tree cracking, enhancing reliability and run-to-run consistency. Overall, these improvements increase model realism, stability, and value for data-driven forest simulations.
Summary of 2026-01 for EvoEngine (edisonlee0212/EvoEngine): Implemented advanced tree dynamics with adaptive settings and multi-tree support (Elm, Oak, Spruce), including rot–moisture interaction, leaf health metrics, and fungus competition dynamics. Added leaf drop mechanics and strengthened structural integrity evaluation through improved moisture handling. Expanded parameterization and logging to enable broader experimentation across Elm, Oak, and Spruce configurations. Fixed a core stability issue related to internal tree cracking, enhancing reliability and run-to-run consistency. Overall, these improvements increase model realism, stability, and value for data-driven forest simulations.
For 2025-11, EvoEngine (edisonlee0212/EvoEngine) delivered substantial progress in dynamic strand simulation by introducing crack pattern modeling and moisture parameter improvements. The work focused on refining collision handling and segment-interaction optimizations to increase realism, stability, and performance in dynamic strand simulations. The outcomes support higher fidelity in complex scenes, reduce runtime instability during deformations, and provide a cleaner, more maintainable codebase for future physics features.
For 2025-11, EvoEngine (edisonlee0212/EvoEngine) delivered substantial progress in dynamic strand simulation by introducing crack pattern modeling and moisture parameter improvements. The work focused on refining collision handling and segment-interaction optimizations to increase realism, stability, and performance in dynamic strand simulations. The outcomes support higher fidelity in complex scenes, reduce runtime instability during deformations, and provide a cleaner, more maintainable codebase for future physics features.
Apr 2025 monthly summary for EvoEngine (edisonlee0212/EvoEngine). Focused on delivering realistic fungus and rot propagation with performance and visualization improvements that directly drive engineering realism and business value for ecosystem simulations.
Apr 2025 monthly summary for EvoEngine (edisonlee0212/EvoEngine). Focused on delivering realistic fungus and rot propagation with performance and visualization improvements that directly drive engineering realism and business value for ecosystem simulations.

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