For years, scientists have tried to solve the engineering obstacle of duplicating the nuclear fusion that occurs naturally in the sun. However, achieving fusion on Earth has remained an elusive challenge until now. Researchers think that AI can solve the nuclear fusion problem and unlock the secrets to sustainable fusion reactors.
Researchers at the Princeton Plasma Physics Laboratory are the first to demonstrate how artificial intelligence can be used to predict and thus avoid potentially catastrophic instabilities occurring in a fusion device. Their work shows the ability of AI to guide plasma and make a significant leap in the development of fusion energy at the same time faced with a great challenge.
Highlights: AI Stabilizes Fusion Power
- Machine learning can rapidly analyze data, identify patterns, and adapt to enhance control over fusion reactions in stellarators and tokamaks.
- AI has successfully avoided magnetic disruptions that destabilize fusion plasma in two tokamak reactors operating in high-confinement mode.
- Researchers are using AI to optimize stellarator design, accelerate complex physics codes, and streamline heat flux modeling for next-generation tokamaks.
- Successful real-time control was demonstrated at the DIII-D tokamak fusion reactor.
- Machine learning models integrated with experimental data aim to reveal optimal plasma confinement methods for commercial-scale fusion reactors.
“There are instabilities in plasma that can lead to severe damage to the fusion device. We can’t have those in a commercial fusion vessel,” added Egemen Kolemen. “Our work advances the field and shows that artificial intelligence could play an important role in managing fusion reactions going forward, avoiding instabilities while allowing the plasma to generate as much fusion energy as possible,”
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The AI Solution: Prediction and Prevention
The researchers trained an AI system on data from past experiments at the DIII-D National Fusion Facility in San Diego. The AI could then forecast potential tearing mode instabilities and disruptions in the magnetic field lines that allow the plasma to escape up to 300 milliseconds in advance during live fusion experiments.
With this early warning, the AI controller adjusted key operating parameters like the plasma shape and input heating to prevent the instabilities from forming and disrupting the plasma.
“By learning from past experiments, rather than incorporating information from physics-based models, the AI could develop a final control policy that supported a stable, high-powered plasma regime in real time, at a real reactor,” said research leader Egemen Kolemen, associate professor at Princeton.
Overcoming Complexity with AI
Even with the world’s most powerful supercomputers, precisely modeling the turbulent, multiscale dynamics of fusion plasma is complex. The researchers acknowledge challenges in scaling up and generalizing the AI controller.
- Powerful magnetic fields struggle to contain superheated plasma over 100 million degrees Celsius in donut-shaped tokamak devices
- Instabilities causing disruptions in the magnetic fields and allowing the plasma to escape. This have been a major roadblock to achieving sustained fusion burn.
- Mimicking real-world conditions requires extremely complex computational codes that run slowly even on advanced supercomputers.
- Balancing the tradeoff between precision and speed when optimizing codes using machine learning models.
- Integrating multiple high-fidelity physics codes and vast experimental datasets to create accurate simulations.
- Overcoming instabilities like edge-localized modes that can damage reactor components in larger, hotter commercial reactors.
Unlocking AI-Powered Fusion’s Potential
Despite the challenges ahead, the researchers are optimistic about AI’s role in commercially viable fusion power plants to generate abundant clean energy.
“Eventually, it may be more than just a one-way interaction of scientists developing and deploying these AI models,” said Kolemen. “By studying them in more detail, they may have certain things that they can teach us too about the underlying physics.“
With AI taking an increasingly prominent role, researchers think AI can solve nuclear fusion problems. They aim to take the path toward harnessing the fierce power of fusion on Earth may finally start to burn brighter.
Source: Engineers use AI to wrangle fusion power for the grid
