# High-order fluid model for streamer discharges: I. Derivation of model and transport data

Dujko, S., Markosyan, A.H., White, R., and Ebert, U.
(2013)
*High-order fluid model for streamer discharges: I. Derivation of model and transport data.*
Journal of Physics D: applied physics, 46 (47). 475202. pp. 1-17.

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## Abstract

Streamer discharges pose basic problems in plasma physics, as they are very transient, far from equilibrium and have high ionization density gradients; they appear in diverse areas of science and technology. This paper focuses on the derivation of a high-order fluid model for streamers. Using momentum transfer theory, the fluid equations are obtained as velocity moments of the Boltzmann equation; they are closed in the local mean energy approximation and coupled to the Poisson equation for the space charge generated electric field. The high-order tensor in the energy flux equation is approximated by the product of two lower order moments to close the system. The average collision frequencies for momentum and energy transfer in elastic and inelastic collisions for electrons in molecular nitrogen are calculated from a multi-term Boltzmann equation solution. We then discuss, in particular, (1) the correct implementation of transport data in streamer models; (2) the accuracy of the two-term approximation for solving Boltzmann's equation in the context of streamer studies; and (3) the evaluation of the mean-energy-dependent collision rates for electrons required as an input in the high-order fluid model. In the second paper in this sequence, we will discuss the solutions of the high-order fluid model for streamers, based on model and input data derived in this paper.

Item ID: | 32877 |
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Item Type: | Article (Research - C1) |

ISSN: | 1361-6463 |

Date Deposited: | 07 May 2014 02:33 |

FoR Codes: | 02 PHYSICAL SCIENCES > 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics > 020201 Atomic and Molecular Physics @ 80% 02 PHYSICAL SCIENCES > 0204 Condensed Matter Physics > 020405 Soft Condensed Matter @ 20% |

SEO Codes: | 97 EXPANDING KNOWLEDGE > 970102 Expanding Knowledge in the Physical Sciences @ 100% |

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