CONSTRUCTING EQUILIBRIUM OF PLASMA MAGNETIC CONFINEMENT THROUGH THE APPLICATION OF PHYSICS-INFORMED NEURAL NETWORKS

• Main Author: Harry Yudha Pratama, Muchamad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/77648
• Institution: Institut Teknologi Bandung

Plasma magnetic confinement is a crucial aspect of fusion research, aiming to achieve stable and controlled conditions for nuclear fusion reactions. In this study, we focus on investigating the dynamics of plasma instabilities and constructing equilibrium solutions within the framework of the magnetohydrodynamics (MHD) equation. Furthermore, we propose an innovative approach by implementing Physics-Informed Neural Networks (PINN) to solve the MHD equilibrium equation, thereby offering a computationally efficient and accurate solution method. The first objective of this research is to construct and analyze the instability of plasma magnetic confinement. By incorporating the principles of magnetohydrodynamics (MHD), the research aims to analyze and understand the mechanisms behind plasma instabilities. The second objective is to develop equilibrium solutions of the MHD equation. Equilibrium states play a critical role in studying plasma stability and confinement. By employing PINN, the research aims to accurately solve the equilibrium equation, taking into account the complex interactions between fluid dynamics and electromagnetic fields. This will facilitate the construction of stable and controlled plasma states. The outcomes of this research will provide valuable insights into the instability of plasma magnetic confinement and contribute to the development of advanced techniques for achieving stable and controlled plasma states. The application of PINN to the equilibrium equation will demonstrate its potential as a promising tool for solving complex plasma physics problems. Ultimately, this work will pave the way for improved plasma confinement and advancements in fusion energy research.