Artificial Intelligence Speeds Up the Artificial Sun Project — AI Software to Find Holy Grail in Fusion Energy
William Tang is a principal research physicist at the U.S. Department of Energy’s (๐ฃ๐ฎ๐ค) Princeton Plasma Physics Laboratory (๐ฏ๐ฏ๐ฏ๐ซ), he leads a team of scientists that uses Artificial intelligence to develop clean, virtually limitless fusion energy.
Fusion, which drives the sun and stars, is that generates energy. It is very important to forecast disruptions — the sudden loss of confinement of plasma particles and energy to make commercial fusion energy work.
Disruptions are that can halt fusion reactions and damage the doughnut-shaped tokamaks that house the reactions. Researchers are using Deep Learning techniques for ๐ฐ๐ธ to predict disruptions accurately and even preventing disruptions from happening in the first place.
Image by U.S. Department of Energy from the United States - 425 003 001, Public Domain, Link
Fusion, which drives the sun and stars, is that generates energy. It is very important to forecast disruptions — the sudden loss of confinement of plasma particles and energy to make commercial fusion energy work.
Disruptions are that can halt fusion reactions and damage the doughnut-shaped tokamaks that house the reactions. Researchers are using Deep Learning techniques for ๐ฐ๐ธ to predict disruptions accurately and even preventing disruptions from happening in the first place.
With that level of accuracy and that amount of time, people running the machine would have time to either mitigate the disruption by cooling the plasma or even by finding a way to avoid it entirely
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| Cutaway diagram of the International Thermonuclear Experimental Reactor (๐จ๐ณ๐ค๐ฑ) the largest tokamak in the world, which began construction in 2013 and is projected to begin operation in 2035. It is intended as a demonstration that a practical fusion reactor is possible, and will produce 500 megawatts of power. The blue human figure at the bottom shows the scale. |
Image by U.S. Department of Energy from the United States - 425 003 001, Public Domain, Link