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Unlocking the secrets of fusion’s core with AI-enhanced simulations
- Nathan Howard, a principal research scientist at MIT, uses AI-enhanced simulations to study fusion reactions.
- He is part of the MFE-IM group at the MIT Plasma Science and Fusion Center.
- Howard and his team aim to predict plasma behavior in fusion devices using simulations and machine learning.
- Their research helps in making smarter design choices for fusion technology.
- In a recent study, Howard used simulations to confirm the performance of ITER, the world's largest experimental fusion device.
- By adjusting operating setups, Howard discovered ways to increase energy output with less energy input, improving efficiency.
- ITER aims to yield 500 megawatts of fusion power and be ten times more energy efficient than external heating.
- Howard's use of high-fidelity simulations like CGYRO and machine learning tools like PORTALS enhances predictions of fusion device performance.
- By refining operating conditions and leveraging surrogates, Howard demonstrates the potential for more efficient fusion reactions.
- Efforts to optimize ITER's performance through simulations and AI-driven models show promise for the future of fusion energy.
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