Update 09/2024 -- Contact me for access to the notebooks here!
I completed my NASA Ames internship this week with a presentation to Ames leadership alongside my team.
For the past few months, I worked with a team of researchers looking into sustainable aviation fuel. I developed 3 Jupyter Notebooks to explore and visualize their data:
1. Sustainable Aviation Fuel (SAF) Emissions Dashboard
Provides analysis of emissions from different SAFs, focusing on chemical compositions, combustion properties, and resultant emissions like CO2, NOx, and particulate matter. Enables comparison of different fuels' environmental impacts, supporting further SAF research.
- Data Sources: Emission data from NASA Ames and partner facilities; chemical analysis data for SAF types (FT-SPK, HEFA-SPK).
- Tools: Pandas, NumPy, SciPy for preprocessing, statistical analysis, and basic correlation analysis between fuel composition and emission levels. Matplotlib and Seaborn were used within Jupyter to create interactive visualizations, such as heatmaps and plots that update dynamically with user inputs.
- Insights: Highlighted a 20% reduction in NOx emissions when using HEFA-SPK compared to conventional jet fuel, helping direct future research.
2. Contrail Formation and Climate Impact Modeling Dashboard
Explores contrail formation and climate impact by visualizing atmospheric data and comparing fuel types to evaluate their effects on contrail persistence and climate impact.
- Data Sources: Atmospheric data from NASA’s DC-8 and remote sensing, including temperature, pressure, humidity, and ice particle size distribution.
- Tools: xarray, Dask for managing large, multidimensional atmospheric data; PyProj for geospatial transformations. Created interactive maps using Plotly and IPywidgets within Jupyter Notebooks, allowing users to explore various atmospheric conditions and their impacts on contrail formation.
- Insights: The dashboard showed that under certain atmospheric conditions, specific SAFs reduced persistent contrail formation by 10%, helping inform climate-related aviation strategies.
3. Fuel Efficiency and Performance Exploration Dashboard
Explores fuel efficiency and performance of different aircraft models, including advanced designs like the Transonic Truss-Braced Wing (TTBW) and the X-57 Maxwell electric aircraft.
- Data Sources: Wind tunnel data, CFD simulations, flight test results, and material performance data.
- Tools: OpenFOAM for CFD simulations; Python integration in Jupyter for processing output data. Plotly.
- Insights: Visualized key patterns in fuel efficiency across different wing designs and biofuel types to direct research.
Note:
The code for these dashboards is available on my GitHub on request, but the data is proprietary.