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DOE OSTI · 1595816

Liquid Metal Diagnostics

Abstract

Liquid metal (LM) plasma-facing components (PFCs) (LM-PFCs) within next-generation fusion reactors are expected to enhance plasma confinement, facilitate tritium breeding, improve reactor thermal efficiency, and withstand large heat and particle fluxes better than solid components made from tungsten, molybdenum, or graphite. Some LM divertor concepts intended for long-pulse operation at >20 MW/m 2 incorporate thin (~1 cm), fast-moving (~5 to 10 m/s), free-surface flows. Such systems will require a range of diagnostics to monitor and control the velocity, flow depth, temperature, and impurity concentration of the LM. As such, this paper will highlight technologies developed for the fission and casting/metallurgical industries that can be adapted to meet the needs of LM-PFC research. This paper is divided into four major parts. The first part will look at noncontact flowmeter technologies that are suitable for high-temperature alkali metal systems. These technologies include rotating Lorentz-force flowmeters for bulk flow rate measurements and particle tracking techniques for surface velocity measurements. Second, this paper will detail the operation of a new inductive level sensor that can be used within free-surface LM-PFCs. This robust level sensor can be mounted below the substrate that supports the LM, so it is simple to install and is protected from the damaging conditions inside a fusion reactor. It has been shown that this level sensor can be calibrated using either numerical or experimental techniques. Third, distributed temperature sensors based on fiber-optic technologies will be discussed. This advanced measurement technique provides temperature data with high spatial resolution and has recently been successfully tested in LM systems. Last, diagnostics to measure impurity concentration, such as electrochemical cells, plugging meters, and spectroscopic systems, will be addressed.

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BibTeXRIS

Hvasta, M. G., Bruhaug, G., Fisher, A. E., Dudt, D., Kolemen, E.. 2019-11-18. Liquid Metal Diagnostics. https://doi.org/10.1080/15361055.2019.1661719

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