Fusion energy has long been seen as the ultimate clean-energy solution, promising nearly unlimited power. However, the journey to making it a reality has been fraught with challenges. Xie Huasheng, a fusion theorist and plasma simulation expert, believes that the industry now has a concrete way to reduce its costly trial-and-error process through improved software. Traditional fusion simulation software has been plagued by an “impossible triangle” of issues: being either accurate but computationally demanding, fast but unreliable, or too simplistic for accurate predictions. Xie asserts that we are at a pivotal moment, with advancements in artificial intelligence and refined mathematical models significantly enhancing research efficiency. In April, Xie launched VeloAlpha, a start-up in Beijing, to develop “FusionAlpha,” a simulator designed to allow developers to test reactor designs virtually, akin to electronic design automation software used in the semiconductor industry. Fusion, the reaction that powers the sun, involves forcing light atomic nuclei to collide and merge, releasing vast amounts of energy. To replicate this on Earth, scientists must heat fuel into a hot, electrically charged gas called plasma and maintain its stability for the reaction to sustain itself.
Can AI Help Overcome Fusion Energy Software Challenges?
