Physics

Edge Turbulence and “Blobs”: Could Smaller Be Better?

Who?

Matthew Ko, Research Intern
Princeton Plasma Physics Laboratory
matthewko@verizon.net

What?

Magnetic fusion is a highly studied potential source of energy in the future. In magnetic fusion, fuel particles are formed into a highly energetic plasma and confined using magnetic fields in a tokamak (a doughnut-shaped magnetic “bottle”). The confined plasma is heated; the fuel particles fuse, and a large quantity of energy is released.

One of the most significant issues impacting current attempts to develop magnetic fusion into a viable source of energy is edge turbulence in the plasma. Controlling the turbulent behavior of filaments of plasma (“blobs”) is essential to any tokamak, as it impacts plasma confinement. This turbulence, acting like a leak in the tokamak, creates problems for the efficiency of the tokamak – the leaking of the plasma outside the magnetic confinement degrades the plasma containment, and can be problematic in maintaining a steady-state plasma. Moreover, when blobs exit the magnetic confinement field and come into contact with the vessel wall, impurities enter the plasma, causing further plasma performance degradation. This research focuses on using database software to analyze empirical data and compare that data with current blob theory. The goal is to better understand blob behavior in order to improve plasma performance.

How?

This experiment used fast 2-D camera data, captured with a Phantom v710 camera, at the National Spherical Torus Experiment (NSTX), a fusion reactor located at the Princeton Plasma Physics Laboratory. The camera was mounted just above the outer mid-plane of NSTX and produced images from a 25 x 25 cm region. This camera data was visualized by using blob tracking software. This, along with the use of a blob database created to compile blob data, characterized over 15,000 blobs for 20-30 milliseconds of various plasma pulses. Information was gathered on Blob Time, Radial Velocity, Size, Position (X), and Position (Y). Blob Size is a measurement of normalized deuterium red light emission, and therefore is a function of plasma density and temperature. Both the blob database and Microsoft Excel were used to plot these variables against one another to determine correlations and dependencies between variables.

Why?

From over 85,000 data points compiled using database software, the plots show evidence that, on average, as blob size increases, radial velocity increases. The correlation is not necessarily linear. It is, however, significant in increasing the practicality of magnetic fusion because the main problem of edge turbulence arises from blobs moving out of the plasma. The implications of this research show that due to their lower radial velocity, smaller blobs would be better than bigger blobs at improving energy confinement in tokamaks.

Comparison to a theoretical approach was also considered. Russian theorist S.I. Krasheninnikov, in his 2001 paper “On scrape off layer plasma transport,” predicts the positive relationship between radial velocity and blob size using theory. The empirical data here agrees with his equation. Agreement between blob theory and experimental data creates the foundations for future research in meeting the final goal of edge turbulence reduction.

With both theory and experiment agreeing on the positive correlation between blob size and radial velocity, plasma physicists can now use this relation to attempt to reduce edge turbulence. For example, a method, such as splitting the blobs, can be devised to reduce the size of blobs. Doing so would reduce the average radial velocity, and thus increase magnetic confinement in the fusion device. The development of an empirical formula for radial velocity would be useful, and especially interesting to compare and contrast to theoretical equations. Another suggestion for future research is using a similar method of determining new relationships between variables that affect magnetic confinement. The advantage of the database is the ability to compile a large number of data points relative to other methods, greatly increasing result reliability.

Keywords

blob, velocity, database

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