Fusion energy, long considered a potential answer to global energy problems, relies on the magnetic confinement method to contain ultra-high temperature plasma within a magnetic field. This approach is at the forefront of fusion reactor technology.
The key to realizing this method of power generation lies in the ability to predict and control the complex behavior of fusion plasma. Traditional methods have struggled with the complexity of plasma flow and various influencing factors like heating, fuel supply, impurities, and neutral particles.
The research group, which includes Assistant Professors Naoki Kenmochi and Hisamichi Funaba, Professors Masayuki Yokoyama and Masaki Osakabe from NIFS, and Professor Genta Ueno of the Institute of Statistical Mathematics, has overcome these challenges with the development of a novel control system. This system, capable of optimizing predictive models through real-time observations, represents a major leap in fusion reactor technology.
Central to this development is ASTI (Assimilation System for Toroidal plasma Integrated simulation), a data assimilation system tailored for fusion plasmas. Data assimilation, a mathematical method commonly used in large-scale simulations like weather forecasting, integrates observed information to reconcile differences between simulations and reality.
By incorporating control functions into this framework, ASTI enables digital twin control of fusion plasmas. This allows real-time adaptation of simulation models to the actual behavior of fusion plasma, facilitating accurate predictions and control based on these predictions.
The system's effectiveness was proven at the Large Helical Device (LHD), the world's leading superconducting plasma experimental facility in Japan. The LHD, equipped with a high-power electron cyclotron resonance heating device and advanced measurement systems like real-time Thomson scattering, provided an ideal environment for this groundbreaking experiment.
Researchers controlled the electron temperature of the actual plasma, optimizing the predictive model based on observed electron density and temperature profiles. This led to the successful demonstration of predictive control of fusion plasma by a digital twin, a first of its kind.
This new control approach is set to become foundational in fusion reactor control, addressing critical challenges like plasma density and temperature profile control, and managing unmeasured variables such as heat escape from the plasma. The results, published in Scientific Reports, a journal of the Nature publishing group, underline the potential of this technology in revolutionizing fusion power generation.
While this experiment represents an initial step in digital twin control of fusion plasmas, its significance cannot be overstated. It lays the groundwork for advanced control solutions essential for fusion power generation, such as plasma profile control and avoiding sudden disappearance phenomena. Plans are underway to expand this control system and conduct further demonstrations at the LHD and other experimental devices globally.
The implications of this data assimilation-based control method extend beyond fusion plasma control. It provides a foundation for adaptive predictive control in scenarios where high accuracy prediction through simulation alone is challenging. This approach could potentially address various societal issues involving uncertain factors, like road traffic and river water level control.
Assistant Professor Morishita, reflecting on the achievement, stated, "I believe that this research is challenging but important in the realization of fusion power generation. It was also a good opportunity for me, who specializes in numerical model calculations, to experience fusion plasma experiments for the first time and to realize the difference between reality and simulation. In the future, I would like to establish this control system as a control foundation for fusion reactors."
Research Report:First application of data assimilation-based control to fusion plasma
Related Links
National Institute for Fusion Science
Powering The World in the 21st Century at Energy-Daily.com
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