
Worked on the MOLONARI1D repository to expand modeling capabilities for coupled heat and water flow in geological columns. Delivered new features including heat source integration via a configurable parameter, updated data visualizations to display results in Celsius, and refreshed documentation to reflect these enhancements. Applied Python and Jupyter Notebooks for scientific computing, focusing on code refactoring and numerical method improvements to increase clarity, modularity, and maintainability. Addressed core stability by fixing calculation bugs in temperature stratification and improving initialization logic for model columns. The work resulted in more robust simulations, streamlined onboarding, and a cleaner codebase for future development.
November 2024 — Key features delivered, bugs fixed, and core stability improvements in the MOLONARI1D project, with focused efforts to expand modeling capability, improve numerical methods, and enhance maintainability. Key features were integrated into core modules and demos, with visualization updated to Celsius and documentation refreshed to reflect heat source functionality. Core refactoring and numerical method enhancements improved clarity and modularity, enabling more robust simulations of heat and water flow in geological columns. Stability fixes addressed critical calculation issues in T_stratified and Column initialization, reducing risk of incorrect IDs and cell counts during initialization. Overall impact includes expanded modeling capabilities, more reliable and interpretable simulations, and a cleaner codebase that supports faster onboarding and future feature work. Technologies demonstrated include Python refactoring, numerical methods for coupled heat/water transport, data visualization updates, and proactive documentation practices, all contributing to increased business value through enhanced capability and maintainability.
November 2024 — Key features delivered, bugs fixed, and core stability improvements in the MOLONARI1D project, with focused efforts to expand modeling capability, improve numerical methods, and enhance maintainability. Key features were integrated into core modules and demos, with visualization updated to Celsius and documentation refreshed to reflect heat source functionality. Core refactoring and numerical method enhancements improved clarity and modularity, enabling more robust simulations of heat and water flow in geological columns. Stability fixes addressed critical calculation issues in T_stratified and Column initialization, reducing risk of incorrect IDs and cell counts during initialization. Overall impact includes expanded modeling capabilities, more reliable and interpretable simulations, and a cleaner codebase that supports faster onboarding and future feature work. Technologies demonstrated include Python refactoring, numerical methods for coupled heat/water transport, data visualization updates, and proactive documentation practices, all contributing to increased business value through enhanced capability and maintainability.

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