Official Submission of Team "ReconXploration:" for NASA Space Apps Challenge 2023 participating in the challenge “Magnetic Reconnection”
Magnetic reconnection is a process that can occur almost anywhere that a magnetic field is found. In a reconnection event, the magnetic field lines are squeezed together somehow and spontaneously reconfigure themselves. This releases energy. When it occurs near the surface of the Sun, such an event powers giant solar flares that can release thousands of millions of tonnes of electrically charged particles into space.
Magnetic reconnection, a natural process in space physics, is not inherently bad but can have adverse effects. It can trigger solar flares and geomagnetic storms, impacting communication systems, power grids, and satellites. Additionally, it poses potential radiation risks to astronauts during space travel.
The program addresses the challenge of analyzing complex interplanetary magnetic field (IMF) data from various missions to determine the frequency and impact of magnetic reconnection events, which is critical for understanding solar wind's influence on our space environment. It simplifies this analysis, providing valuable insights into space weather effects for both researchers and the general public.
Users gain a deeper understanding of space weather and its potential effects on technology and daily life, empowering them to make informed decisions and preparations. Scientists benefit from efficient analysis of magnetic reconnection events, enhancing their research on solar wind interactions and aiding in space weather forecasting.
The opportunity lies in developing an accessible and robust computer program that translates complex data analysis into actionable insights about magnetic reconnection, fostering an increased understanding of space weather's effects on both the general public and scientific researchers.
MAKE THE MAGNETIC RECONNECTION VISIBLE WITH A MODEL SO THAT WE CAN:
- Determine the magnitude of the magnetic field, the speed & and power generated by solar winds.
IN OMNI DATA, WE TRAINED THE MODEL USING RNN (RECURRENT NEURAL NETWORK) BASED UPON LINEAR REGRESSION It requires 3 parameters to predict the speed and magnitude of the magnetic fields. Those parameters are:
- YEAR
- PROTON DENSITY
- TEMPERATURE
IN DSCOVR DATA, WE TRAINED THE MODEL USING RNN (RECURRENT NEURAL NETWORK) BASED ON LTSM (LONG SHORT-TERM MEMORY) It only requires speed which is calculated from the OMNI data to calculate the power generated by the solar winds
Understanding solar wind impacts and their correlation with magnetic field data contributes to the advancement of clean energy technologies and aligns with SDG 7, which seeks to ensure access to affordable, reliable, sustainable, and modern energy for all.
Creating innovative technologies and infrastructure to analyze space data and understand solar wind impacts aligns with SDG 9, which aims to build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation.
Studying the solar wind and its effects on the space environment is crucial for understanding climate patterns and potential climate change impacts. This aligns with SDG 13, which focuses on taking urgent action to combat climate change and its impacts.
Collaboration between space agencies, researchers, and technology developers to create the mentioned program exemplifies partnerships that contribute to the achievement of multiple SDGs. SDG 17 emphasizes the importance of partnerships for sustainable development.
It will facilitate informed decision-making, improve space weather forecasting, and contribute to a safer and more prepared approach to potential space weather impacts.
Our solution empowers people to prepare and adapt, ultimately fostering a safer environment in an increasingly technology-dependent world.
Look at our Research Document, please!
Look at our presentation slides, please !
