Hydrodynamic Models for Multicomponent Plasmas with Collisional-Radiative Kinetics
Abstract
Energy and space propulsion are two of the largest applied research areas requiring contributions from fundamental physical sciences, due to the growing worldwide demand in energy and continuing interests in expanding the frontier of deep space exploration. One of the common thrust areas in these two disciplines is plasma physics, the study of the motion of charged particles and their interaction with the electromagnetic field. The characterization of these plasma systems requires a comprehensive understanding of the physics of charged particles, collisional and radiative interactions among these particles, and how they interact with the electromagnetic field. This dissertation presents some advances in the development of hydrodynamic models for plasma modeling and simulations in highly non-equilibrium conditions. Expressed in the form of conversation laws, these governing equations are solved by a finite volume discretization with a high-order reconstruction procedure and a multi-stage time integration method. High-fidelity collisional-radiative (CR) models are constructed by taking into account various elementary processes responsible for the excitation and ionization kinetics. The accuracy of the CR model is benchmarked against different experimental shock tube data, and yields satisfactory agreement for a wide range of flow conditions. A mechanism reduction scheme, based on a level grouping approach, is derived to lower the complexity of the CR kinetics while maintaining sufficient accuracy to capture the nonequilibrium dynamics of the plasma kinetics. The method is shown to be more accurate and efficient than standard level grouping approach, and is suitable for multidimensional flow calculations. Although the hydrodynamic or fluid approach offers a convenient way to model the system, it requires some assumptions on the time and length scales, which in some case might be violated. Fortunately, small deviations from these assumptions can still be captured.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2014
- Accession Number
- AD1001156
Entities
People
- Hai P. Le
Organizations
- Air Force Research Laboratory