Jannis Teunissen

The inception of pulsed discharges in air: simulations in background fields above and below breakdown

We investigate discharge inception in air, in uniform background electric fields above and below the breakdown threshold. We perform 3D particle simulations that include a natural level of background ionization in the form of positive and � O 2 ions. In background fields below breakdown, we use a strongly ionized seed of electrons and positive ions to enhance the field locally. In the region of enhanced field, we observe the growth of positive streamers, as in previous simulations with 2D plasma fluid models. The inclusion of background ionization has little effect in this case. When the background field is above the breakdown threshold, the situation is very different. Electrons can then detach from � O 2 and start ionization avalanches in the whole volume. These avalanches together create one extended discharge, in contrast to the ‘double-headed’ streamers found in many fluid simulations.

Streamer discharges can move perpendicularly to the electric field

Streamer discharges are a primary mode of electric breakdown in thunderstorms and high voltage technology; they are generally believed to grow along electric field lines. However, we here give experimental and numerical evidence that streamers can propagate nearly perpendicularly to the background electric field. These streamers are guided by pre-ionization that is orders of magnitude lower than the ionization density in a streamer channel, hardly affecting the background field. Positive streamers could be guided in nitrogen with 0.5% of oxygen or less, but not in air. This observation also tests the role of photoionization in gas mixtures with varying nitrogen–oxygen ratio.

A time scale for electrical screening in pulsed gas discharges

The Maxwell time is a typical time scale for the screening of an electric field in a medium with a given conductivity. We introduce a generalization of the Maxwell time that is valid for gas discharges: the ionization screening time, that takes the growth of the conductivity due to impact ionization into account. We present an analytic estimate for this time scale, assuming a planar geometry, and evaluate its accuracy by comparing with one- and three-dimensional numerical simulations. We investigate the minimum plasma density required to prevent the growth of streamers with local field enhancement, and we discuss the effects of photoionization and electron detachment on ionization screening. Our results can help to understand the development of pulsed discharges, for example nanosecond pulsed discharges at atmospheric pressure or halo discharges in the lower ionosphere.

3D PIC-MCC simulations of discharge inception around a sharp anode in nitrogen/oxygen mixtures

We investigate how photoionization, electron avalanches and space charge affect the inception of nanosecond pulsed discharges. Simulations are performed with a 3D PIC-MCC (particle-in-cell, Monte Carlo collision) model with adaptive mesh refinement for the field solver. This model, whose source code is available online, is described in the first part of the paper. Then we present simulation results in a needle-to-plane geometry, using different nitrogen/oxygen mixtures at atmospheric pressure. In these mixtures non-local photoionization is important for the discharge growth. The typical length scale for this process depends on the oxygen concentration. With 0.2% oxygen the discharges grow quite irregularly, due to the limited supply of free electrons around them. With 2% or more oxygen the development is much smoother. An almost spherical ionized region can form around the electrode tip, which increases in size with the electrode voltage. Eventually this inception cloud destabilizes into streamer channels. In our simulations, discharge velocities are almost independent of the oxygen concentration. We discuss the physical mechanisms behind these phenomena and compare our simulations with experimental observations.

Comparing plasma fluid models of different order for 1D streamer ionization fronts

We evaluate the performance of three plasma fluid models: the first order reaction-drift-diffusion model based on the local field approximation; the second order reaction-drift-diffusion model based on the local energy approximation and a recently developed high order fluid model by Dujko et al (2013 J. Phys. D 46 475202) We first review the fluid models: we briefly discuss their derivation, their underlying assumptions and the type of transport data they require. Then we compare these models to a particle-in-cell/Monte Carlo (PIC/MC) code, using a 1D test problem. The tests are performed in neon and nitrogen at standard temperature and pressure, over a wide range of reduced electric fields. For the fluid models, transport data generated by a multi-term Boltzmann solver are used. We analyze the observed differences in the model predictions and address some of the practical aspects when using these plasma fluid models.

3-D Particle Modeling of Positive Streamer Inception From a Needle Electrode in Supercritical Nitrogen

Positive streamers need a source of free electrons ahead of them to propagate. Here we investigate a possible source of these electrons in high density media: field ionization. Zeners model is used to obtain the field ionization rate of free electrons from impurities. Including this effect, we simulate the inception of positive streamers in supercritical N2, in a needle-to-plane electrode geometry. Our 3-D particle simulation shows how the discharge branches into positive streamer channels around the electrode.

Afivo: A framework for quadtree/octree AMR with shared-memory parallelization and geometric multigrid methods

Abstract Afivo is a framework for simulations with adaptive mesh refinement (AMR) on quadtree (2D) and octree (3D) grids. The framework comes with a geometric multigrid solver, shared-memory (OpenMP) parallelism and it supports output in Silo and VTK file formats. Afivo can be used to efficiently simulate AMR problems with up to about 1 0 8 unknowns on desktops, workstations or single compute nodes. For larger problems, existing distributed-memory frameworks are better suited. The framework has no built-in functionality for specific physics applications, so users have to implement their own numerical methods. The included multigrid solver can be used to efficiently solve elliptic partial differential equations such as Poisson’s equation. Afivo’s design was kept simple, which in combination with the shared-memory parallelism facilitates modification and experimentation with AMR algorithms. The framework was already used to perform 3D simulations of streamer discharges, which required tens of millions of cells. Program summary Program Title: Afivo Program Files doi: http://dx.doi.org/10.17632/5y43rjdmxd.1 Licensing provisions: GPLv3 Programming language: Fortran 2011 External routines/libraries: Silo (LLNL) Nature of problem: Performing multiscale simulations, especially those requiring a fast elliptic solver. Solution method: Provide a framework for parallel simulations on adaptively refined quadtree/octree grids, including a geometric multigrid solver. Unusual features: The framework uses shared-memory parallelism (OpenMP) instead of MPI.

Simulating streamer discharges in 3D with the parallel adaptive Afivo framework

We present an open-source plasma fluid code for 2D, cylindrical and 3D simulations of streamer discharges. The code is based on the Afivo framework, which features adaptive mesh refinement on quadtree/octree grids, geometric multigrid methods for Poissons equation, and OpenMP parallelism. We describe the numerical implementation of a fluid model of the drift-diffusion-reaction type, combined with the local field approximation. Then we demonstrate its functionality with 3D simulations of long positive streamers in nitrogen in undervolted gaps. Three examples are presented. The first one shows how a stochastic background density affects streamer propagation and branching. The second one focuses on the interaction of a streamer with preionized regions, and the third one investigates the interaction between two streamers. The simulations use up to 108 grid cells and run in less than a day; without mesh refinement they would require more than grid cells.

Tumor classification with MALDI-MSI data of tissue microarrays: A case study

With mass spectrometry imaging (MSI) on tissue microarrays (TMAs) a large number of biomolecules can be studied for many patients at the same time, making it an attractive tool for biomarker discovery. Here we investigate whether lymph node metastasis can be predicted from MALDI-MSI data. Measurements are performed on TMAs and then filtered based on spectral intensity and the percentage of tumor cells, after which the resulting data for 122 patients is further preprocessed. We assume differences between patients with and without metastasis are expressed in a limited number of features. Two univariate feature selection methods are applied to reduce the dimensionality of the MALDI-MSI data. The selected features are then used in combination with three classifiers. The best classification scores are obtained with a decision tree classifier, which classifies about 72% of patients correctly. Almost all the predictive power comes from a single peak (m/z 718.4). The sensitivity of our classification approach, which can be generically used to search for biomarkers, is investigated using artificially modified data.

Propagation of a Positive Streamer Toward a Dielectric Tip in Pure Nitrogen and in Air Under Voltage Pulses With Subnanosecond Rise Time

We simulate a positive streamer discharge approaching a dielectric tip (e.g., of a dielectric rod) under a voltage pulse with a subnanosecond rise time. In air, the streamer reaches the tip, whereas in nitrogen, it does not.