Publication details
Electric field determination in air plasmas from intensity ratio of nitrogen spectral bands: I. Sensitivity analysis and uncertainty quantification of dominant processes
| Authors | |
|---|---|
| Year of publication | 2018 |
| Type | Article in Periodical |
| Magazine / Source | PLASMA SOURCES SCIENCE & TECHNOLOGY |
| MU Faculty or unit | |
| Citation | |
| Web | The ratio of the spectral band intensities of the first negative and second positive spectral systems of molecular nitrogen is a well recognized method for indirect determination of the electric field. |
| Doi | http://dx.doi.org/10.1088/1361-6595/aad663 |
| Keywords | electric field; air kinetics; sensitivity analysis; uncertainty quantification; optical emission spectroscopy; cross-sections; nitrogen spectral bands |
| Description | The ratio of the spectral band intensities of the first negative and second positive spectral systems of molecular nitrogen is a well recognized method for indirect determination of the electric field. It is applied for various plasmas, e.g. barrier and corona discharges for industrial applications or geophysical plasmas occurring in the Earth's atmosphere. The method relies on the dependence of the intensity ratio R(E/N) of selected bands on the reduced electric field strength. Both experimental and theoretical approaches have been used to determine this dependence, yet there still is a rather large spread in the data available in literature. The primary aim of this work is to quantify the overall uncertainty of the theoretical R(E/N) dependence and identify the main sources of this uncertainty. As the first step we perform sensitivity analysis on a full N-2/O-2 plasma kinetics model to find a minimal set of processes that are influential for the R(E/N) dependence. It is found to be in agreement with simplified kinetic models generally used. Subsequently, we utilize Monte Carlo-based uncertainty quantification to provide a confidence band for the electric field obtained from the theoretical R(E/N) dependence. Finally, subsequent steps are proposed to significantly reduce the uncertainty of the method. |
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