Monte Carlo Simulation of Electron Swarms in H2

Hunter, S. R.

doi:10.1071/ph770083

Cited by 28 publications

(9 citation statements)

References 5 publications

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“…showing how W includes a contribution from non-conservative processes. These simulations also yield the longitudinal and transversal diffusion coefficients D L and D T obtained as [48]…”

Section: Monte Carlo Methodsmentioning

confidence: 99%

Electron transport parameters in CO₂: scanning drift tube measurements and kinetic computations

Vass

Korolov

Loffhagen

et al. 2017

Plasma Sources Sci. Technol.

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This work presents transport coefficients of electrons (bulk drift velocity, longitudinal diffusion coefficient, and effective ionization frequency) in CO 2 measured under time-of-flight conditions over a wide range of the reduced electric field, 15 Td ≤ E/N ≤ 2660 Td in a scanning drift tube apparatus. The data obtained in the experiments are also applied to determine the effective steady-state Townsend ionization coefficient. These parameters are compared to the results of previous experimental studies, as well as to results of various kinetic computations: solutions of the electron Boltzmann equation under different approximations (multiterm and density gradient expansions) and Monte Carlo simulations. The experimental data extend the range of E/N compared with previous measurements and are consistent with most of the transport parameters obtained in these earlier studies. The computational results point out the range of applicability of the respective approaches to determine the different measured transport properties of electrons in CO 2 . They demonstrate as well the need for further improvement of the electron collision cross section data for CO 2 taking into account the present experimental data.

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“…showing how W includes a contribution from non-conservative processes. These simulations also yield the longitudinal and transversal diffusion coefficients D L and D T obtained as [48]…”

Section: Monte Carlo Methodsmentioning

confidence: 99%

Electron transport parameters in CO₂: scanning drift tube measurements and kinetic computations

Vass

Korolov

Loffhagen

et al. 2017

Plasma Sources Sci. Technol.

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“…The drift velocity of electrons in hydrogen gas has been well documented [23][24][25][26][27][28][29][30]. The mobility of electrons in hydrogen gas has also been well measured [31][32][33][34][35][36][37].…”

Section: Plasma Loadingmentioning

confidence: 98%

Pressurized rf cavities in ionizing beams

Freemire

Tollestrup

Yonehara

et al. 2016

Phys. Rev. Accel. Beams

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A muon collider or Higgs factory requires significant reduction of the six dimensional emittance of the beam prior to acceleration. One method to accomplish this involves building a cooling channel using high pressure gas filled radio frequency cavities. The performance of such a cavity when subjected to an intense particle beam must be investigated before this technology can be validated. To this end, a high pressure gas filled radio frequency (rf) test cell was built and placed in a 400 MeV beam line from the Fermilab linac to study the plasma evolution and its effect on the cavity. Hydrogen, deuterium, helium and nitrogen gases were studied. Additionally, sulfur hexafluoride and dry air were used as dopants to aid in the removal of plasma electrons. Measurements were made using a variety of beam intensities, gas pressures, dopant concentrations, and cavity rf electric fields, both with and without a 3 T external solenoidal magnetic field. Energy dissipation per electron-ion pair, electron-ion recombination rates, ion-ion recombination rates, and electron attachment times to $SF_6$ and $O_2$ were measured.Comment: 15 p

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“…However, since these discharges are inherently complex, and the particle velocity distributions can be non-Maxwellian, there has been a considerable effort to develop self-consistent kinetic models with no assumptions about the distribution functions. Monte Carlo methods have been used extensively in swarm simulations [4][5][6][7][8][9]. The conventional method of calculating the time between collisions for each particle using a random number can be generalized into efficient algorithms, especially when the null collision method is also used [6,10].…”

Section: Introductionmentioning

confidence: 99%

A Monte Carlo collision model for the particle-in-cell method: applications to argon and oxygen discharges

Vahedi

Surendra²

1995

Computer Physics Communications

928

697

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In order to use particle-in-cell (PIC) simulation codes for modeling collisional plasmas and self-sustained discharges, it is necessary to add interactions between charged and neutral particles. In conventional Monte Carlo schemes the time or distance between collisions for each particle is calculated using random numbers. This procedure allows for efficient algorithms but is not compatible with PIC simulations where the charged particle trajectories are all integrated simultaneously in time. A Monte Carlo collision (MCC) package including the null collision method has been developed, as an addition to the usual PIC charged particle scheme which will be discussed here. We will also present results from simulations of argon and oxygen discharges, and compare our argon simulation results with experimental measurements.

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Monte Carlo Simulation of Electron Swarms in H2

Cited by 28 publications

References 5 publications

Electron transport parameters in CO₂: scanning drift tube measurements and kinetic computations

Electron transport parameters in CO₂: scanning drift tube measurements and kinetic computations

Pressurized rf cavities in ionizing beams

A Monte Carlo collision model for the particle-in-cell method: applications to argon and oxygen discharges

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Monte Carlo Simulation of Electron Swarms in H2

Cited by 28 publications

References 5 publications

Electron transport parameters in CO2: scanning drift tube measurements and kinetic computations

Electron transport parameters in CO2: scanning drift tube measurements and kinetic computations

Pressurized rf cavities in ionizing beams

A Monte Carlo collision model for the particle-in-cell method: applications to argon and oxygen discharges

Contact Info

Product

Resources

About

Electron transport parameters in CO₂: scanning drift tube measurements and kinetic computations

Electron transport parameters in CO₂: scanning drift tube measurements and kinetic computations