Visualization of plasma shape in the LHD-type helical fusion reactor, FFHR, by a deep learning technique

• Published in: Journal of Visualization Vol. 24; no. 6; pp. 1141 - 1154
• Main Authors: Hu, Kunqi, Koyamada, Koji, Ohtani, Hiroaki, Goto, Takuya, Miyazawa, Junichi
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Science and Business Media LLC 01.12.2021; Springer Berlin Heidelberg; Springer Nature B.V
• Subjects: Annotations; Artificial neural networks; Classical and Continuum Physics; Computer Imaging; Controlled fusion; Cross-sections; Cubes; Deep learning; Electromagnetic fields; Engineering; Engineering Fluid Dynamics; Engineering Thermodynamics; Fusion reactors; Heat and Mass Transfer; Machine learning; Magnetic fields; Magnetism; Pattern Recognition and Graphics; Plasma; Regular Paper; Scalars; Subject specialists; Three dimensional analysis; Three dimensional models; Vision; Deep learning; 3D model; Visualization; Plasma shape

A magnetic field is used to confine the plasma to achieve controlled fusion. Therefore, since the movement of the plasma follows magnetic field lines, a plurality of magnetic field lines is calculated from electromagnetic field simulation results in a fusion reactor. Because of the complicated distr...