Physics-Based-Adaptive Plasma Model for High-Fidelity Numerical Simulations

Abstract

A physics-based-adaptive plasma model and an appropriate computational algorithm are developed to numerically simulate plasma phenomena in high fidelity. %The physics-based-adaptive plasma model is dynamically refined based on the local conditions to provide uniform model fidelity throughout the domain at all times of the simulation. The physics-based-adaptive plasma model can be dynamically refined based on the local plasma conditions to increase model fidelity uniformity throughout the domain at all times of the simulation. %The adaptive plasma model uses continuum representations of the plasma, which include a kinetic Boltzmann model for the highest fidelity, multi-fluid plasma models (13N-moment and 5$N$-moment), and single-fluid MHD models for the lowest fidelity. The adaptive plasma model uses continuum representations of the plasma, which include a kinetic Vlasov model for the highest fidelity, multi-fluid 5$N$-moment plasma model, and single-fluid MHD model for the lowest fidelity. The models include evolution equations for the electromagnetic fields, electron species, ion species, and neutral species. A nodal discontinuous Galerkin finite element method is implemented and is coupled with various implicit and explicit Runge-Kutta methods. Various model coupling techniques are investigated for a 5$N$-moment multi-fluid models with a Vlasov-Maxwell model, and a 5$N$-moment two-fluid model with an MHD model. Continuum plasma models using consistent normalizations and identical spatial representations provide straightforward and accurate coupling between the models. %The solution approach offers the potential for high-order accuracy and computational efficiency. The solution approach offers high-order accuracy and computational efficiency. Target compute platforms are heterogeneous computer architectures using a compute model that minimizes data movement.