A novel method based on combining Direct Simulation Monte Carlo (DSMC) and Discrete Velocity Method (DVM) representations of the velocity distribution functions in velocity space is applied to rarefied ionized gas flows in order to study its efficiency and accuracy. The objective is to improve the efficiency of modeling of flows where trace populations have a significant effect on the flow physics. Numerical results are obtained for a 0-dimensional flow of a Ar/Ar+ /e− mixture and compared with the BOLSIG+ solver.
For high voltage electrical devices, prevention of high voltage breakdown is critical for device function. Use of polymeric encapsulation such as epoxies is common, but these may include air bubbles or other voids of varying size. The present work aimed to model and experimentally determine the size dependence of breakdown voltage for voids in an epoxy matrix, as a step toward establishing size criteria for void screening. Effects were investigated experimentally for both one-dimensional metal/epoxy/air/epoxy/metal gap sizes from 50 μm to 10 mm, as well as spherical voids of 250 μm, 500 μm, 1 mm and 2 mm sizes. These experimental results were compared to modified Paschen curve and particle-in-cell discharge models; minimum breakdown voltages of 6 - 8.5 kV appeared to be predicted by 1D models and experiments, with minimum breakdown voltage for void sizes of 0.2 - 1 mm. In a limited set of 3D experiments on 250 μm, 500 μm, 1 mm and 2 mm voids within epoxy, the minimum breakdown voltages observed were 18.5 - 20 kV, for 500 μm void sizes. These experiments and models are aimed at providing initial size and voltage criteria for tolerable void sizes and expected discharge voltages to support design of encapsulated high voltage components.
In the present research, a new method for simulation of rarefied gas flows is proposed, a velocity-space hybrid of both a DSMC representation of particles and a discrete velocity quasi-particle representation of the distribution function. The hybridization scheme is discussed in detail, and is numerically verified for two test-cases: the BKW relaxation problem and a stationary Maxwellian distribution. It is demonstrated that such a velocity-space hybridization can provide computational benefits when compared to a pure discrete velocity method or pure DSMC approach, while retaining some of the more attractive properties of discrete velocity methods. Further possible improvements to the velocity-space hybrid approach are discussed.
3D Particle-In-Cell Direct Simulation Monte Carlo (PIC-DSMC) simulations of cm-sized devices cannot resolve atomic-scale (nm) surface features and thus one must generate micron-scale models for an effective “local” work function, field enhancement factor, and emission area. Here we report on development of a stochastic effective model based on atomic-scale characterization of as-built electrode surfaces. Representative probability density distributions of the work function and geometric field enhancement factor (beta) for a sputter-deposited Pt surface are generated from atomic-scale surface characterization using Scanning Tunneling Microscopy (STM), Atomic Force Microscopy (AFM), and Photoemission Electron Microscopy (PEEM). In the micron-scale model every simulated PIC-DSMC surface element draws work functions and betas for many independent “atomic emitters”. During the simulation the field emitted current from an element is computed by summing each “atomic emitter's” current. This model has reasonable agreement with measured micron-scale emitted currents across a range of electric field values.
The purpose of this paper is to characterize the need for improved predictive capabilities in low-temperature plasma (LTP) science, and to identify possible means of accomplishing this. While these means may constitute an initiative of their own, we consider these ideas to have widespread importance to discovery plasma science. Therefore, it is our hope that these ideas are more generally incorporated in future work.
We report on the verification of elastic collisions in EMPIRE-PIC and EMPIRE-Fluid in support of the ATDM L2 V&V Milestone. The thermalization verification problem and the theory behind it is presented along with an analytic solution for the temperature of each species over time. The problem is run with both codes under multiple parameter regimes. The temperature over time is compared between the two codes and the theoretical results. A preliminary convergence analysis is performed on the results from EMPIRE-PIC and EMPIRE-Fluid showing the rate at which the codes converge to the analytic solution in time (EMPIRE-Fluid) and particles (EMPIRE-PIC).