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Related Experiment Video

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Building Langmuir Probes and Emissive Probes for Plasma Potential Measurements in Low Pressure, Low Temperature Plasmas

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Reduced model of plasma evolution in hydrogen discharge capillary plasmas.

G J Boyle¹, M Thévenet¹, J Chappell²

¹Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, 22607 Hamburg, Germany.

Physical Review. E

|August 20, 2021

Summary

A new model simplifies plasma temperature evolution in discharge capillary devices by using an ordinary differential equation instead of complex magnetohydrodynamic simulations. This offers a computationally efficient tool for analyzing plasma conditions.

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Area of Science:

Plasma Physics
Computational Physics
Engineering

Background:

Discharge capillary devices are crucial for various applications.
Accurate modeling of plasma behavior within these devices is essential.
Existing magnetohydrodynamic (MHD) simulations are computationally intensive.

Purpose of the Study:

To develop a simplified model for plasma temperature evolution in discharge capillary devices.
To replace complex partial differential equations with a single ordinary differential equation.
To enhance computational efficiency for plasma condition analysis.

Main Methods:

Developed an analytic quasistatic description for radial temperature variation.
Incorporated Ohmic heating, heat loss, ionization, and recombination effects.
Utilized local thermal equilibrium conditions to link radial and average temperature evolution.

Main Results:

Successfully replaced standard MHD simulations with a single ordinary differential equation.
Achieved good agreement between model calculations and 1D MHD simulations for hydrogen plasmas.
Demonstrated the model's ability to predict on-axis plasma temperature and electron density.

Conclusions:

The developed model provides a computationally efficient and simple tool for evaluating plasma conditions.
This model is suitable for computationally expensive applications like long-term simulations and parameter scans.
The model facilitates optimization studies, including those using machine-learning techniques.