gaelpoette/COURS_COLLAB_2024
Dec 2024 – Dec 2024
1 Month active
Languages Used
C++Python
Technical Skills
Algorithm ImplementationC++ DevelopmentChemical Kinetics SimulationData VisualizationNumerical AnalysisNumerical Methods
Haytham El Bada
PROFILE
Haytham El Bada
During December 2024, Haytham Elbada developed an advanced numerical methods framework for the gaelpoette/COURS_COLLAB_2024 repository, focusing on chemical kinetics simulation. He implemented a Runge-Kutta 4th order (RK4) solver in C++ to accurately model species densities in chemical reactions, integrating robust numerical analysis and algorithm implementation techniques. The framework included features for exporting simulation results, enabling seamless data visualization and supporting iterative model development. Haytham’s work demonstrated depth in both numerical methods and data handling, providing a stable foundation for chemical simulation workflows. The project leveraged C++ and Python, emphasizing reliable simulation accuracy and efficient data-driven analysis.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
104,971
Activity Months1
Your Network
14 peopleSame Organization
@enseirb-matmeca.fr1
Work History
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for gaelpoette/COURS_COLLAB_2024: Delivered an advanced numerical methods framework featuring an RK4 solver for chemical simulations, with data export for visualization. This work enhances simulation accuracy and provides a ready-to-visualize data pipeline, enabling data-driven decision making and faster iteration on chemical kinetics models. No major bugs fixed this month.
2 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for gaelpoette/COURS_COLLAB_2024: Delivered an advanced numerical methods framework featuring an RK4 solver for chemical simulations, with data export for visualization. This work enhances simulation accuracy and provides a ready-to-visualize data pipeline, enabling data-driven decision making and faster iteration on chemical kinetics models. No major bugs fixed this month.
December 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability70.0%
Architecture70.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Algorithm ImplementationC++ DevelopmentChemical Kinetics SimulationData VisualizationNumerical AnalysisNumerical Methods
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