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Introduction to Plasma Physics and Controlled Fusion
This complete introduction to plasma physics and controlled fusion by one of the pioneering scientists in this expanding field offers both a simple and intuitive discussion of the basic concepts of this subject and an insight into the challenging problems of current research. In a wholly lucid manner the work covers single-particle motions, fluid equations for plasmas, wave motions, diffusion and resistivity, Landau damping, plasma instabilities and nonlinear problems. For students, this outstanding text offers a painless introduction to this important field; for teachers, a large collection of problems; and for researchers, a concise review of the fundamentals as well as original treatments of a number of topics never before explained so clearly. This revised edition contains new material on kinetic effects, including Bernstein waves and the plasma dispersion function, and on nonlinear wave equations and solitons. For the third edition, updates was made throughout each existing chapter, and two new chapters were added; Ch 9 on “Special Plasmas” and Ch 10 on Plasma Applications (including Atmospheric Plasmas).
504 pages, Hardcover
Published December 29, 2015
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January 2, 2025
Plasma, often dubbed the "fourth state of matter," is a quasi-neutral ensemble of charged particles (ions and electrons) and neutral particles exhibiting collective behaviors due to long-range Coulomb interactions. Unlike solids, liquids, or gases, plasmas are defined not merely by the thermal kinetic energy of particles but by intricate electromagnetic dynamics, including Debye shielding, plasma oscillations, and magnetohydrodynamic (MHD) phenomena. These properties enable plasma to support a multitude of waves—such as Langmuir waves, Alfvén waves, and whistler modes—and nonlinear structures like solitons, shocks, and turbulence. Plasma is ubiquitously found in both terrestrial environments (e.g., lightning, fluorescent lamps) and astrophysical settings (e.g., stellar coronae, intergalactic mediums), forming the backbone of space and fusion sciences.Computational plasma physics leverages numerical methods and algorithms to solve the inherently nonlinear and multiscale equations governing plasma dynamics. The field's theoretical cornerstone lies in frameworks such as the Boltzmann equation for particle kinetics, the Vlasov-Maxwell equations for collisionless plasma, and fluid-based approaches like the MHD equations for macroscopic analysis. These frameworks address challenges arising from phenomena like Landau damping, gyrokinetic turbulence, and magnetic reconnection.
To model these complexities, computational plasma physics employs three primary methodologies:
Particle-in-Cell (PIC) Methods: These simulate individual particle trajectories in self-consistent electromagnetic fields, coupling Lagrangian particle dynamics with Eulerian field solvers. PIC methods are particularly adept at resolving kinetic effects, such as velocity-space instabilities, at the cost of computational expense due to particle noise.Fluid Models: Simplified approaches like single-fluid MHD or multi-fluid formulations approximate plasma as a continuous medium. While computationally efficient, these models are constrained by assumptions of quasi-neutrality, isotropic pressure, and negligible kinetic effects.Hybrid Models: These combine the kinetic description of specific particle species (e.g., ions) with fluid treatments of others (e.g., electrons), bridging the gap between fidelity and efficiency.
Modern computational plasma research encompasses diverse applications, such as optimizing magnetic confinement in tokamaks for nuclear fusion, studying magnetosphere-ionosphere coupling in space weather prediction, and exploring plasma-material interactions in industrial processes. Emerging tools include machine learning algorithms to accelerate simulations, high-performance computing for multi-scale coupling, and adaptive mesh refinement to dynamically resolve spatial and temporal gradients.
To model these complexities, computational plasma physics employs three primary methodologies:
Particle-in-Cell (PIC) Methods: These simulate individual particle trajectories in self-consistent electromagnetic fields, coupling Lagrangian particle dynamics with Eulerian field solvers. PIC methods are particularly adept at resolving kinetic effects, such as velocity-space instabilities, at the cost of computational expense due to particle noise.Fluid Models: Simplified approaches like single-fluid MHD or multi-fluid formulations approximate plasma as a continuous medium. While computationally efficient, these models are constrained by assumptions of quasi-neutrality, isotropic pressure, and negligible kinetic effects.Hybrid Models: These combine the kinetic description of specific particle species (e.g., ions) with fluid treatments of others (e.g., electrons), bridging the gap between fidelity and efficiency.
Modern computational plasma research encompasses diverse applications, such as optimizing magnetic confinement in tokamaks for nuclear fusion, studying magnetosphere-ionosphere coupling in space weather prediction, and exploring plasma-material interactions in industrial processes. Emerging tools include machine learning algorithms to accelerate simulations, high-performance computing for multi-scale coupling, and adaptive mesh refinement to dynamically resolve spatial and temporal gradients.
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