Topic: Space Science

Meeting virtually three times per week, 22 UC Merced students engaged with LLNL mentors and peers to address a real-world challenge problem, using machine learning to identify potentially hazardous asteroids that could pose an existential threat to humanity.

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Livermore teams are applying innovative data analysis and interpretation techniques to advance fundamental science research.

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In support of NASA’s Planetary Defense Coordination Office, researchers are creating 3D models and using LLNL's ALE3D code to produce simulations of hypothetical asteroid impact scenarios.

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Testbed Environment for Space Situational Awareness software helps to track satellites and space debris and prevent collisions.

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