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- SH51D-1190: Optimizing the Parameters of the WSA Model Using Particle Filtering
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Board 1190‚ Hall EFG (Poster Hall)NOLA CC
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Gavin Pinto, New Jersey Institute of Technology (First Author, Presenting Author)
Daniel da Silva, NASA Goddard Space Flight Center
Shaela Jones-Mecholsky, Catholic University of America
Charles Arge, NASA Goddard Space Flight Center
The Wang-Sheeley-Arge model is a physics-based model that predicts solar wind. It utilizes two models to estimate solar wind speed. The first model calculates the Sun's magnetic field from its surface up to a certain distance, while the second model extends the field beyond that surface. Both models are shaped as layered circles around the sun, and can be adjusted by their radii. This project finds the optimal radii values using a method called particle filtering, an optimization technique for estimating any system.The particle filter was implemented using Python and was run with different settings. We compared two runs based on 27 days of data. One run selected optimal radii based on the entire 27-day period, while the other did separate optimizations for each of four 7-day periods, each using the previous period’s results to start the next. This project compared the results from both runs to decide how to structure the time periods for particle filtering for optimal results.
Additionally, we developed a Python script for organizations to run the particle filter. It allows them to run the particle filter at a specified configuration, and will save the results of each run in designated folders on their system.
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