FR1.1: KINETIC-FLUID MODELS

FR1.1: KINETIC-FLUID MODELS

Goal: Identify physics-based criteria for selecting kinetic and fluid models for different plasma species
based on local plasma properties.

Challenges: Identify physics-based criteria for selecting kinetic and fluid models for different plasma species based on local plasma properties.

Background: Plasma simulations are challenging because i) high spatial resolution required for part of the system (e.g., sheaths, shock layers) makes spatially uniform computational meshes impractical; ii) kinetic solvers (both particle- and grid-based) are expensive computationally; iii) disparate time scales for electrons
and ions create long simulation times if both time scales are resolved, and iv) coupling electromagnetics with charge transport results in highly non-linear problems.

Proposed Research: We will develop statistical particle-based methods and direct numerical solutions of the kinetic equations (Boltzmann, Vlasov, Wigner, etc.) that describe transport processes in classical and quantum physics at the most fundamental level.

Integration with Transformational Technology: These advances will aid several disciplines, including Space Weather forecasting (TT5), optimizing plasma reactor design (TT3 and TT1), and plasma-surface interactions (TT3 and TT4). The proposed activities will also be integrated with the experimental research and fundamental studies in FR2.

Impacts: The development and implementation of adaptive kinetic-fluid models will increase predictive capabilities and efficiency of plasma simulations affecting all TT1-5 projects.

FR1.1a: Kinetic solvers with adaptive mesh in phase space

We develop grid-based and particle-based kinetic solvers with adaptive mesh in configuration (physical), velocity, and phase space. For grid-based solvers, we either split velocity and physical spaces (for phase space dimensions > 3) or use problem symmetry to reduce dimensionality of phase space and develop non-split solvers (for phase space dimensions < 3).

FR1.1b: Implicit fluid models for reactive plasma

Coupled implicit solvers with time-scale separation methodology.

FR1.1c: Hybrid models for gaseous plasma

Adaptive Mesh & Algorithm Refinement (AMAR) framework allows identifying criteria for dynamically selecting kinetic and fluid models for electrons, ions, and neutral species in different part of systems. The development of adaptive kinetic-fluid models increases predictive capabilities and efficiency of plasma simulations.

FR1.1d: Development of particle-based computational models for plasma
simulations

• We develop particle-based and hybrid particle/continuum solver based on the Direct Simulation Monte Carlo (DSMC) method and collision radiation model
• We optimize schemes for coarse graining of excited energy states of ions in the collision radiation model
• Apply hybrid kinetic-fluid models to study laser ablation of metallic and semiconductor targets with bursts of short and ultrashort pulses
• Compare computational results with experiments on laser ablation and expansion of laser-produced plasma