Abstract

Modern experimental nuclear physics programs that utilize advanced superconducting devices require refrigeration below the lambda temperature of helium (2.1768 K) and involve sub-atmospheric helium at some point in the process. They typically operate between 1.8 and 2.1 K (16 to 40 mbar) and can require refrigeration ranging from tens to thousands of watts. These processes are very energy intensive, requiring roughly 850 W/W even for large and well-designed refrigerators, though they can easily require much more. Adiabatic expansion of sub-cooled liquid helium to these sub-atmospheric pressures will result in a two-phase mixture with a large liquid to vapor density ratio. Since there are no practical expanders to handle this condition, a counter flow heat exchanger is used to cool the super-critical helium supply using the returning sub-atmospheric helium. Typically, the super-critical helium exiting this 4.5 K to 2-K counter flow heat exchanger is throttled across an expansion valve to a sub-atmospheric pressure. This is a substantial irreversibility, typically 13 percent of the enthalpy difference between the load supply and return. A significant process improvement is theoretically obtainable by handling the exergy loss across the expansion valve supplying the flow to the load in a simple but different manner. The exergy loss can be minimized by allowing the supply flow pressure to decrease to a sub-atmospheric pressure concurrent with heat exchange with the sub-atmospheric flow from the load. This dissertation work encompasses testing of a practical implementation using a Collin’s type heat exchanger to investigate the overall performance, as well as, the optimum selections of independent process parameters and how this affects the heat exchanger size distribution. The thermodynamics of heat exchange with a significant pressure drop for a non-ideal fluid are investigated, in regards to an equivalent expansion efficiency pseudo-property, a practical process expansion efficiency equivalence and an overall 2-K system performance improvement expectation. Theoretically predicted optimum independent process parameters are compared to those measured.

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